With the rapidly increasing volume of cyber-attacks over the past years due to the new working-from-home paradigm, protecting hosts, networks, and individuals from cyber threats is in higher demand than ever. One promising solution are Provenance-based Intrusion Detection Systems (PIDS), which correlate host-based security logs to generate provenance graphs that describe the causal relationship between system entities. PIDS have shown significant potential in enhancing detection performance and reducing false alarms compared to traditional Intrusion Detection Systems (IDS). Rule-based approaches used in PIDS utilize expert-defined rule sets to identify known malicious patterns in provenance graphs. Although these rule-based techniques have been widely applied, they can only detect known attack patterns, are heavily dependent on the quality of the rules, and creating rules manually is time-consuming. To address these shortcomings, this study proposed two novel techniques: the Multi-level Attack Description Model (MADM) for describing attack patterns at multiple granularity levels and the Provenance-enabled Automated Rule Generation and Matching Framework (PARGMF) to generate rules deterministically and promptly. We evaluated the proposed approaches using the DARPA OpTC dataset, complemented by a practical case study. This case study involved a prototype extension for the CAPEv2 sandbox environment, demonstrating the real-world applicability of our approaches. Our results demonstrate, firstly, that PARGMF generates rules deterministically with an average processing time of only 13.11 s compared to multiple hours or even days for manual rule creation by security experts. Secondly, through generalization of attack descriptions, MADM enhanced the robustness of rules by 21.9% for Behavioural Attack Description (BAD) and 25% for Structural Attack Description (SAD) compared to approaches without generalization. Another added benefit compared to existing approaches is that PARGMF also generates differential graphs to support security experts’ timely validation of security alarms.

Big data is generally captured by sensor networks in various industrial and manufacturing sectors; this big data is transmitted by mobile devices and Internet of Things (IoT) devices through the 5G mobile networks. 5G mobile edge computing is generally integrated with artificial intelligence (AI) in order to perform data mining for big data. 5G mobile edge computing attempts to help the industries to increase product quality, improve robustness and reliability of manufacturing processes, enhance manufacturing productivity and effectiveness, and reduce production costs. Recently, cryptocurrencies such as Bitcoin and Litecoins are used in virtual transactions by many financial sectors. Blockchain is integrated with the cryptocurrencies. Blockchain attempts to ensure security, trust and privacy of the virtual transactions, while centralized authorities or management are not necessary to be involved. Blockchain connects all transaction parties in order to monitor and verify each transaction. It reduces transaction risks and financial fraud without the involvement of centralized authorities or management. While blockchain is implemented in mobile devices and IoT devices, data trust and honesty can be guaranteed in the 5Gmobile networks. When the captured data ismore reliable, accurate datamining and analysis can be performed by the 5Gmobile edge computing. This special section focus on 5G mobile edge computing methods in order to perform better data analysis, simulations, and predictions for industrial applications when blockchain is integrated in the 5G mobile networks. We received 30 high quality submissions for this special section on "Blockchain and AI Enabled 5G Mobile Edge Computing." After the review and revision processes, six articles were selected to be published in this valuable document. Those articles are briefly summarized.

As the volume of scientific papers grows rapidly in size, knowledge management for scientific publications is greatly needed. Information extraction and knowledge fusion techniques have been proposed to obtain information from scholarly publications and build knowledge repositories. However, retrieving the knowledge of problem/solution from academic papers to support users on solving specific research problems is rarely seen in the state of the art. Therefore, to remedy this gap, a knowledge-driven solution support system (K3S) is proposed in this paper to extract the information of research problems and proposed solutions from academic papers, and integrate them into knowledge maps. With the bibliometric information of the papers, K3S is capable of providing recommended solutions for any extracted problems. The subject of intrusion detection is chosen for demonstration in which required information is extracted with high accuracy, a knowledge map is constructed properly, and solutions to address intrusion problems are recommended.

Traffic flow forecasting is a useful technology applied to solve traffic congestion problems and to improve transportation mobility. Neural networks related approaches have been applied to develop traffic forecasting models for more than two decades. Since neural networks are sensitivity in parameters selection, selecting appropriate modeling configuration is essential to improve the accuracy and efficiency of traffic flow prediction. However, this is usually conducted by the trial-and-error method, which is very time consuming while involving too many design factors. Therefore, this paper utilizes a robust and systematic optimization approach, the Taguchi method, for obtaining the optimized configuration of the proposed exponential smoothing and extreme learning machine forecasting model. The developed model is applied to real-world data collected from freeways and highways in the United Kingdom and is compared with three existing forecasting models. The results indicate that the Taguchi method is efficient and capable for the forecasting model design and the proposed model with the optimized configuration has superior performance in traffic flow forecasting with approximate 91% and 88% accuracy rate in freeway and highway in both peak and nonpeak traffic periods.

Assortment planning is one of the fundamental and complex decisions for online retailers. The complexity of this problem is increasing while considering demand and supply uncertainties in assortment planning (AP). However, this leads to more efficient results in today's uncertain markets. In this paper, the supplier and E-tailer interactions are modeled by the non-cooperative game theory model. As small-scale online retailers opposed to bricks and mortar usually have lower power in front of suppliers, we propose a Stackelberg or leader-follower game model. First, the supplier as a leader announces its decisions regarding selling price to the E-tailer. Consequently, the E-tailer reacts by determining the purchase quantity, selling price to the customers and assortment size. Various scenarios are presented and analyzed to show the effectiveness of the Stackelberg game model in simulating the interactions between small-scale online retailers and a powerful supplier.

The constant increase in the growth of the cloud market creates new challenges for cloud service providers. One such challenge is the need to avoid possible service level agreement (SLA) violations and their consequences through good SLA management. Researchers have proposed various frameworks and have made significant advances in managing SLAs from the perspective of both cloud users and providers. However, none of these approaches guides the service provider on the necessary steps to take for SLA violation abatement; that is, the prediction of possible SLA violations, the process to follow when the system identifies the threat of SLA violation, and the recommended action to take to avoid SLA violation. In this paper, we approach this process of SLA violation detection and abatement from a risk management perspective. We propose a Risk Management-based Framework for SLA violation abatement (RMF-SLA) following the formation of an SLA which comprises SLA monitoring, violation prediction and decision recommendation. Through experiments, we validate and demonstrate the suitability of the proposed framework for assisting cloud providers to minimize possible service violations and penalties.

We propose an interactive decision-making framework to assist a Customer Service Representative (CSR) in the efficient and effective recognition of customer records in a database with many ambiguous entries. Our proposed framework consists of three integrated modules. The first module focuses on the detection and resolution of duplicate records to improve effectiveness and efficiency in customer recognition. The second module determines the level of ambiguity in recognizing an individual customer when there are multiple records with the same name. The third module recommends the series of feature-related questions that the CSR should ask the customer to enable rapid recognition, based on that level of ambiguity. In the first module, the F-Swoosh approach for duplicate detection is used, and in the second module a dynamic programming-based technique is used to determine the level of ambiguity within the customer database for a given name. In the third module, Levenshtein edit distance is used for feature selection in combination with weights based on the Inverse Document Frequency (IDF) of terms. The algorithm that requires the minimum number of questions to be put to the customer to achieve recognition is the algorithm that is chosen. We evaluate the proposed framework on a synthetic dataset and demonstrate how it assists the CSR to rapidly recognize the correct customer.

The concept of stratification (CST) is a reform in problem solving approaches in computer science introduced and developed by Lotfi Zadeh [1]. In this approach, the target set is a set of the initial states. The environment around the target is then systematically identified and strata around the target are gradually built using the concept of `incremental target enlargement'. We advocate that this approach is useful in different areas; however, it is essential to highlight the potential applicability of the approach by presenting different examples. In this paper illustrative examples in Information Dominance (ID) and in requirement elicitation in contracting, are structured using CST. These examples show the application of the concept in the contexts of logistic informatics and contracting and assists the modelling process. Of particular relevance are Example 4 and 5. Example 4 exposes situations that are not dealt with in the current form of CST. The study, therefore, extends CST by considering the possibility of occasional state repetition while using the same input. Further, a 3D version of CST is structured and examined through example 5. This proposed version of the concept illustrates how the Fuzzy Inference System (FIS) benefits the user when applying CST.

Health, Safety, Environment and Ergonomie (HSEE) are important factors in any organization. An organization always have to assess its compliance in these factors to the required benchmarks and take proactive actions to improve them if required. In this paper, we propose a Fuzzy Cognitive Map-Bayesian network (BN) model in order to assist organizations in doing this process. Fuzzy Cognitive Map (FCM) method is used for constructing graphical model of BN to ascertain the relationships between the inputs and the impact which they will have on the quantified HSEE. Noisy-OR method and EM are used to ascertain the conditional probability between the inputs and quantifying the HSEE value. Using this, we find out the most influential input factor on HSEE quantification which can then be managed for improving an organization's compliance to HSEE. Leveraging the power of Bayesian network in modeling HSEE and augmenting it with FCM is the main contribution of this research work which opens this line of research.

Avoiding ambiguity and fuzziness in the determination of the requirements is a crucial factor in the success of Performance Based Contracting (PBC). To date, there is a research gap because insufficient studies have been undertaken to address this significant issue in the pro-curement process. Previous studies that have been con-ducted on requirement specification and elicitation are limited to software engineering. This study investigates this issue in the procurement process and proposes an integrated framework using Natural Language Pro-cessing (NLP), game theory and fuzzy logic. This re-search contributes to contract theory by opening a new line of research which paves the way for leveraging arti-ficial intelligence techniques in automated or semi-automated contract monitoring.

Effective business planning requires seamless access and intelligent analysis of information in its totality to allow the business planner to gain enhanced critical business insights for decision support. Current business planning tools provide insights from structured business data (i.e. sales forecasts, customers and products data, inventory details) only and fail to take into account unstructured complementary information residing in contracts, reports, user's comments, emails etc. In this article, a planning support system is designed and developed that empower business planners to develop and revise business plans utilizing both structured data and unstructured information conjointly. This planning system activity model comprises of two steps. Firstly, a business planner develops a candidate plan using planning template. Secondly, the candidate plan is put forward to collaborating partners for its revision interleaving deliberation. Planning interleaving deliberation activity in the proposed framework enables collaborating planners to challenge both a decision and the thinking that underpins the decision in the candidate plan. The planning system is modeled using situation calculus and is validated through a prototype development.

Cloud-of-things service providers use various descriptions languages to describe Quality of Service (QoS) attributes. However, existing modelling approaches provide support for modelling static QoS attributes only and lack features to model and reason with dynamic QoS attributes such as response time and availability. This paper presents an event-based approach for monitoring dynamic QoS values and their compliance by modelling the behavior of QoS attributes using an Event Calculus (EC) based framework. The logic based reasoning is then performed to proactively identify the possible QoS violations in future.

The big data research topic has grown rapidly for the past decade due to the advent of the "data deluge". Recent advancements in the literature leverage human computing power known as crowdsourcing to manage and harness big data for various applications. However, human involvement in the completion of crowdsourcing tasks is an error-prone process that affects the overall performance of the crowd. Thus, controlling the quality of workers is an essential step for crowdsourcing systems, which due to unavailability of ground-truth data for any task at hand becomes increasingly challenging. To propose a solution to this problem, in this study, we propose OSQC (Online Statistical Quality Control Framework) for managing the performance of workers in crowdsourcing. OSQC ascertains the worker's performance by using a statistical model and then leverages the traditional statistical control techniques to decide whether to retain a worker for crowdsourcing or to evict him. We evaluate our proposed framework on a real dataset and demonstrate how OSQC assists crowdsourcing to maintain its accuracy.

Building ontology for wireless network intrusion detection is an emerging method for the purpose of achieving high accuracy, comprehensive coverage, self-organization and flexibility for network security. In this paper, we leverage the power of Natural Language Processing (NLP) and Crowdsourcing for this purpose by constructing lightweight semi-automatic ontology learning framework which aims at developing a semantic-based solution-oriented intrusion detection knowledge map using documents from Scopus. Our proposed framework uses NLP as its automatic component and Crowdsourcing is applied for the semi part. The main intention of applying both NLP and Crowdsourcing is to develop a semi-automatic ontology learning method in which NLP is used to extract and connect useful concepts while in uncertain cases human power is leveraged for verification. This heuristic method shows a theoretical contribution in terms of lightweight and timesaving ontology learning model as well as practical value by providing solutions for detecting different types of intrusions.

Service level agreement (SLA) is an essential agreement formed between a consumer and a provider in business activities. The SLA defines the business terms, objectives, obligations and commitment of both parties to a business activity, and in cloud computing it also defines a consumer's request for both fixed and variable resources, due to the elastic and dynamic nature of the cloud-computing environment. Providers need to thoroughly analyze such variability when forming SLAs to ensure they commit to the agreements with consumers and at the same time make the best use of available resources and obtain maximum returns. They can achieve this by entering into viable SLAs with consumers. A consumer's profile becomes a key element in determining the consumer's reliability, as a consumer who has previous service violation history is more likely to violate future service agreements; hence, a provider can avoid forming SLAs with such consumers. In this paper, we propose a novel optimal SLA formation architecture from the provider's perspective, enabling the provider to consider a consumer's reliability in committing to the SLA. We classify existing consumers into three categories based on their reliability or trustworthiness value and use that knowledge to ascertain whether to accept a consumer request for resource allocation, and then to determine the extent of the allocation. Our proposed architecture helps the service provider to monitor the behavior of service consumers in the post-interaction time phase and to use that information to form viable SLAs in the pre-interaction time phase to minimize service violations and penalties.

Cloud computing is a very attractive option for service users and service providers for their businesses because of the benefits it provides. A major concern among service users regarding cloud adoption, however, is the unpredictability of performance in relation to the services provided. Even though guarantees in the form of service-level agreements are provided to users by service providers, real-time service-level degradability remains a critical concern; hence, there is a need for an approach that assists users to manage a service before it fails. The approaches proposed in the literature assess and evaluate the performance of the cloud infrastructure of providers, but this does not guarantee that a given service instance will meet the desired quality level because there may be factors other than the provider's infrastructure that will affect the level of quality of the service instance. In this paper, we present an approach that measures the quality of a service instance in real time and provides important analysis for service users as to whether they will achieve their desired objectives. This analysis also constitutes an important input for service users in the assessment and management of a service to avoid the failure to achieve objectives.

Argumentation is the practice of systematic conscious reasoning involving the construction and evaluation of arguments to justify or support a particular conclusion. This article discusses, compares, contrasts and categorizes existing argumentation-based frameworks and applications as either philosophical or logic-based, and provides critical analysis that emphasizes the structure of arguments and the interactions between them. This review compares and contrasts the frameworks and applications of argumentation-based approaches on Web 2.0 and the Semantic Web, and subsequently highlights the importance and challenges of attaining monological argumentation on the Semantic Web.

Smart grids have created an emerging entity of “prosumer” in the energy value network who not only consumes energy but also generates and shares the green energy with the utility grid. Hence, effective management of prosumers has become pivotal to ensure a long-term, sustainable energy-sharing process. Recently, the concept of a Prosumer Community Group (PCG) has emerged as one of the most promising and effective ways to manage prosumers. However, developing sustainable PCGs is challenging. One of the key challenges in this regard is to assess the contribution made by individual prosumers of a PCG, and find a subset of the most influential prosumers whose behavior would facilitate the long-term sustainability of the PCG. In this paper, we have focused on this challenge and proposed an innovative methodology to assess and rank the prosumers, in order to build an influential membership base. We have assessed the long-term and short-term energy behaviors of prosumers based on multiple evaluation criteria and accordingly decided the ranks of the prosumers, whereby the higher ranked prosumers are deemed to be more influential in enhancing the long-term sustenance of the PCG. Furthermore, we have presented simulation results to verify our proposed methodology. The current literature on smart-grid research field has no work investigating this challenge, making our contribution novel.

SUMMARY Web services provide a standard means for the interoperable operations between electronic devices in a network. The mission of Web service discovery is to seek an appropriate Web service for a service requester on the basis of the service descriptions in Web service advertisements and the service requester's requirements. Nevertheless, the standard language used for encoding service descriptions does not have the capacity to specify the capabilities of a Web service, leading to the problem of ambiguity in the service discovery process. This brings up the vision of Semantic Web Services and Semantic Web Service discovery, which make use of the Semantic Web technologies to enrich the semantics of service descriptions for service discovery. Semantic Web Service matchmakers are the programs or frameworks designed to implement the task of Semantic Web Service discovery and have drawn a significant amount of attention from both academia and industry from the start of this century. In this paper, we conduct a survey of the contemporary Semantic Web Service matchmakers in order to obtain an overview of the state of the art in this research area. We summarize six technical dimensions from the past literature and analyze the typical Semantic Web Service matchmakers mostly developed during the past 4 or 5 years in terms of the six dimensions. By means of this analysis, we gain an understanding of the current research and summarize a series of potential issues to that would provide the foundation for future research in this area.Copyright © 2012 John Wiley & Sons, Ltd.

The main purpose of this paper is to propose a content analysis approach in order to develop an ontology of university social responsibility (USR). The proposed approach comprises four main phases in which two content analyses software have been utilized to extract the main USR components and to identify the domain of this concept. To achieve the goal, the existing body of knowledge of USR definitions and specifications - using a variety of terms - has been considered to identify the main notions of USR and their relationships. The developed ontology can be applied to define a formal, explicit description of the USR concept and to construct a more reliable basis for measurement purposes.

Online learning systems in general and virtual universities in particular received considerable attention and had an increasing growth through two last decades. However, the acceptance and enough support from stakeholders sounds to be the main challenges of this kind of educational systems. Regarding this issue, the recent study is aimed to propose and validate a methodology for measuring social responsibility of virtual universities, by which higher education systems would be able to evaluate how each virtual university is responsible to its stakeholders and it can provide a useful scale to be used for ranking of this higher education institutions. The factors that comprise university social responsibility are inherently fuzzy and subjective in nature; therefore, in this research we propose to make use of Fuzzy Logic for measuring and quantifying this concept. Additionally in this research, based on the identified factors, we will develop ontological manifestations of social responsibility of virtual universities.

Cyber-Physical Systems (CPS) provides a smart infrastructure connecting abstract computational artifacts with the physical world. This paper presents some challenges for developing distributed real-time Cyber-Physical Systems. The focus is on one particular challenge, namely event modelling in distributed real-time CPS. A Web-of-Things based CPS framework for event handling and processing is proposed. To illustrate the application of the proposed framework, a case study for achieving demand response in a smart home is provided.

Over the past two decades, neural networks have been applied to develop short-term traffic flow predictors. The past traffic flow data, captured by on-road sensors, is used as input patterns of neural networks to forecast future traffic flow conditions. The amount of input patterns captured by the on-road sensors is usually huge, but not all input patterns are useful when trying to predict the future traffic flow. The inclusion of useless input patterns is not effective to developing neural network models. Therefore, the selection of appropriate input patterns, which are significant for short-term traffic flow forecasting, is essential. This can be conducted by setting an appropriate configuration of input nodes of the neural network; however, this is usually conducted by trial and error. In this paper, the Taguchi method, which is a robust and systematic optimization approach for designing reliable and high-quality models, is proposed for the purpose of determining an appropriate neural network configuration, in terms of input nodes, in order to capture useful input patterns for traffic flow forecasting. The effectiveness of the Taguchi method is demonstrated by a case study, which aims to develop a short-term traffic flow predictor based on past traffic flow data captured by on-road sensors located on a Western Australia freeway. Three advantages of using the Taguchi method were demonstrated: 1) short-term traffic flow predictors with high accuracy can be designed; 2) the development time for short-term traffic flow predictors is reasonable; and 3) the accuracy of short-term traffic flow predictors is robust with respect to the initial settings of the neural network parameters during the learning phase.

This paper proposes a novel neural network (NN) training method that employs the hybrid exponential smoothing method and the Levenberg-Marquardt (LM) algorithm, which aims to improve the generalization capabilities of previously used methods for training NNs for short-term traffic flow forecasting. The approach uses exponential smoothing to preprocess traffic flow data by removing the lumpiness from collected traffic flow data, before employing a variant of the LM algorithm to train the NN weights of an NN model. This approach aids NN training, as the preprocessed traffic flow data are more smooth and continuous than the original unprocessed traffic flow data. The proposed method was evaluated by forecasting short-term traffic flow conditions on the Mitchell freeway in Western Australia. With regard to the generalization capabilities for short-term traffic flow forecasting, the NN models developed using the proposed approach outperform those that are developed based on the alternative tested algorithms, which are particularly designed either for short-term traffic flow forecasting or for enhancing generalization capabilities of NNs.

A writing genre can be thought of as the style in which the writer chooses to present textual content to the reader. We distinguish four main types of essay genres namely Narrative, Persuasive, Descriptive and Expository. An essay's writing genre can be identified by searching for salient features present within those genres using various Natural Language Processing tools such as Named Entity Recognition, Part of Speech tagging and Sentence Parsing. This paper explains the more common writing genres in student essays and describes the method in which essays in the narrative genre are identified.

Cloud computing has change the strategy of the way of providing distributed services for many business and government agents. Cloud computing delivers a scalable and on demand services for most users in different domains. This new technology brings many challenges to service providers and customers especially for users who already own complicated legacy systems. This paper examines challenges related to the concepts of trust, SLA management, and cloud computing. We focus on SLA definition in cloud computing to achieve the aim of presenting a clear structure of SLA for cloud users and improve the way of building trustworthy relationship between service provider and customer. In this paper, we start with the presenting the importance of cloud computing and the need of SLA for cloud computing. Then, survey of cloud computing architecture is provided. Then, we discuss existing frameworks of service level agreements in different domains such as web services and grid computing. The last part of literature review discusses advantages and limitations of performance measurement models in SOA, distributed systems, grid computing, and cloud services. Finally, we summarize and conclude our work.

Ontology evolution becomes an interesting topic in the semantic web field and increasingly getting research momentum. However, there is still a lack of understanding and support in ontology evolution. In this paper, we focus on an approach for ontology evolution of Software Engineering Ontology (SE Ontology) in multi-site software development setting. An integration of agents with semantic web technology and recommender systems to address communication and co-ordination issues is proposed together with a use of social networks for the purpose of ontology evolution.

Abstract The recent development of Web‐of‐Things (WoT) and Cyber–Physical Systems (CPS) raises a new requirement of connecting abstract computational artifacts with the physical world. This requires both new theories and engineering practices that model cyber and physical resources in a unified framework, a challenge that few current approaches are able to tackle. The solution must break the boundary between the cyber world and the physical world by providing a unified infrastructure that permits integrated models addressing issues from both worlds simultaneously. This paper proposes a framework to integrate WoT and CPS. A case study is presented to demonstrate the advantage of the framework. Copyright © 2010 John Wiley & Sons, Ltd.

Abstract While many researchers have contributed to the field of semantic similarity models so far, we find that most of the models are designed for the semantic network environment. When applying the semantic similarity model within the semantic‐rich ontology environment, two issues are observed: (1) most of the models ignore the context of ontology concepts and (2) most of the models ignore the context of relations. Therefore, in this paper, we present a solution for the two issues, including a novel ontology conversion process and a context‐aware semantic similarity model, by considering the factors of both the context of concepts and relations, and the ontology structure. Furthermore, in order to evaluate this model, we compare its performance with that of several existing models' performance in a large‐scale knowledge base, and the evaluation result preliminarily proves the technical advantage of our model in ontology environments. Conclusions and future works are described in the final section. Copyright © 2010 John Wiley & Sons, Ltd.

Many believe that Cloud will reshape the entire ICT industry as a revolution. In this paper, we aim to pinpoint the challenges and issues of Cloud computing. We first discuss two related computing paradigms - Service-Oriented Computing and Grid computing, and their relationships with Cloud computing. We then identify several challenges from the Cloud computing adoption perspective. Last, we will highlight the Cloud interoperability issue that deserves substantial further research and development.

As Wireless Mesh Networks (WMNs) are newly emerging wireless technologies, they are designed to have huge potential for strengthening Internet deployment and access. However, they are far from mature for large-scale deployment in some applications due to the lack of the satisfactory guarantees on security. The main challenges exposed to the security of WMNs come from the facts of the shared nature of the wireless architecture and the lack of globally trusted central authorities. A well-performed security framework for WMNs will contribute to network survivability and strongly support the network growth. A low-computational and scalable key management model for WMNs is proposed in this paper which aims to guarantee well-performed key management services and protection from potential attacks.

In a recent decade many universities responded to challenges of the internet penetration into the society and economics by simply adding computerized facilities to their existing curriculum services as their e-learning strategy [3] so that the traditional teaching and learning model could be preserved. This e-learning strategy deployment is now being challenged by the emergence of Social Networking System/Site (SNS). In order to evaluate how SNS would have affected current Higher Education System (HES), one needs to look into the inner working of value exchange within a broader societal community to extract relational interactions among its participating components (entities), and substantiate what had been challenged internally of a community to prepare for the external intrusion of SNS in a foreseeable future. In this paper, a triple-entity learning community framework is proposed with its Core Value that glues the participating entities together (Figure 5). Prior to this framework, graduate's employability issues as part of the Core Value are brought to the surface to help educators revise their existing e-learning strategies, so that curriculum content providing educational resources to its clients will be serviced in a more timely and responsive manner.

Cognitive Radio (CR) has been considered as a promising concept for improving the utilization of limited radio spectrum resources for future wireless communications and mobile computing. As cognitive radio network (CRN) is a general wireless heterogeneous network, it is very essential for detecting the misbehaving or false nodes in the network. So in this paper we propose a trust aware model which provides a reliable approach to establish trust for CRN. This approach combines all kinds of trust values together, including the direct trust and indirect trust value for the secondary users. Depending on this trust value, it is decided that whether the secondary user can user the primary user's spectrum band or not. The mathematical results show that our trust model can efficiently take decision for assigning spectrums to the users.

Digital Ecosystem is an innovative high-tech environment with the purpose of supporting the activities among species within the business ecosystem. In this paper, we concern about the research issue of service retrieval within such an environment. Due to the fact that species are heterogeneous and geographically dispersed, to precisely and quickly locate a service provider becomes an issue. In addition, the Digital Ecosystem environment urgently requires the structualization of service information and a set of unified QoS measurement for service ranking and evaluation. In order to unfold the issues in detail, we use the means of case study and literature survey. Eventually we formulate the research issues in this domain and provide a possible solution.

The nature of trust in business relationships is dynamic rather than static. Trust has evolutionary phases or a life cycle. This pattern of evolution can be described as building, maintaining and destroying. Building trust comes at high cost and hard effort. Therefore, once trust has been established in a business relationship, every effort must be made to maintain it. Maintaining trust can be defined as an effort to maximize the benefits of a relationship and to prevent the level of trust from decreasing to the destroying phase. Grounded in state-of-the-art literature, this paper presents current insights for the research into trust maintenance and suggests directions for future research in this field.

The Digital Business Ecosystem (DBE) is the result of the co-evolution of the Business Ecosystem and the Digital Ecosystem. There are numerous approaches and enabling technologies which are used in modeling open business marketplaces and, due to the similarities between the Digital Business environments, they can also help to enable the Digital Business Ecosystem but with some limitations. The complete lifecycle of the DBE can be decomposed into the following phases: formation, evolution and dissipation. In this work, our main focus is on the importance of negotiation in the DBE formation phase and especially on the structure of Contract Net Protocol. We will present an extension to the primitive Contract Net Protocol and name it Contract Net with Quality Protocol (CNQP or Q-Contract Net) to facilitate the negotiation process by adding the quality evaluation steps during the negotiation phase of the DBE formation.

Cloud services are becoming popular in terms of distributed technology because they allow cloud users to rent well-specified resources of computing, network, and storage infrastructure. Users pay for their use of services without needing to spend massive amounts for integration, maintenance, or management of the IT infrastructure. This creates the need for a reliable measurement methodology of the scalability for this type of new paradigm of services. In this paper, we develop performance metrics to measure and compare the scalability of the resources of virtualization on the cloud data centres. First, we discuss the need for a reliable method to compare the performance of cloud services among a number of various services being offered. Second, we develop a different type of metrics and propose a suitable methodology to measure the scalability using these types of metrics. We focus on the visualization resources such as CPU, storage disk, and network infrastructure. Finally, we compare well-known cloud providers using the proposed approach and conclude the recommendations. This type of research will help cloud consumers, before signing any official contract to use the desired services, to ascertain the ability and capacity of the cloud providers to deliver a particular service.

We define a digital ecosystem (DES) as the dynamic and synergetic complex of digital communities consisting of interconnected, interrelated, and interdependent digital species situated in a digital environment that interact as a functional unit and are linked together through actions, information, and transaction flows. The design of DESs requires the integration of a number of different and complementary technologies, including agent-based and self-organizing systems, ontologies, swarm intelligence, ambient intelligence, data mining, genetic algorithms, etc. The integration of multiple technologies and the resulting synergetic effects contribute to the creation of highly complex, dynamic, and powerful systems. The application of DESs within different domains has the power to transform these domains by giving them a more intelligent and a more dynamic nature. In this paper, we illustrate how a DES design methodology can be used to systematically create a Digital Health Ecosystem (DHES). We address the key steps associated with the DES design and focus specifically on the use of the electronic health records within the DHES. The design methodology framework illustrated in this paper serves as a navigating tool during the design of DHESs.

In a business interaction, transactional risk highlights the uncertainty associated in not achieving the desired outcomes. The assessment of transactional risk gives the interacting user the different levels of failure in achieving its desired outcomes and the consequences that it can experience. In a business interaction, the consequences that can be experienced pertain to the financial resources invested to achieve the desired outcomes. The level of financial loss that could be experienced plays a very important role in the interacting userpsilas decision to form a business interaction. The level of financial loss is dependent on the different types of uncertain events associated with the business interaction. In this paper, we will propose a methodology by which the interacting user in an e-business interaction can capture the different types of uncertainties and ascertain the financial risk that could be experienced from it.

Self-healing key distribution mechanism can be utilized for distributing session keys over an unreliable network. A self-healing key distribution scheme using bilinear pairings is proposed in this paper. As far as we know, it is the first pairing-based authenticated self-healing key distribution scheme. The scheme achieves a number of excellent properties. Firstly, the users can check the integrity and correctness of the ciphertext before carrying out more complex key recovery operations thus fruitless work can be avoided. Secondly, the scheme is collusion-free for any coalition of non-authorized users. Thirdly, the private key has nothing to do with the number of revoked users and can be reused as long as it is not disclosed. Finally, the storage overhead for each user is a constant.

This paper reports on results from a pilot study that used Bloompsilas taxonomy to observe cognition levels during software inspections conducted by undergraduate computer science and software engineering students. Cognition levels associated with three different code inspection techniques were investigated. These were the ad hoc, abstraction driven, and checklist-based reading strategies. Higher cognition levels were observed when using inspection techniques that utilise a more structured reading process. This result highlights the importance of introducing novice programmers to structured code reading strategies. Findings suggest that teaching different software inspection techniques throughout software courses, beginning with structured techniques, is an excellent way to build a studentpsilas critical software reading and analysis skills.

In this paper, we propose an Internet public Web service matching approach that paves the way for (semi-)automatic service mashup. We first provide the overview of the solution, which requires a detailed review of two fundamental models - schema/graph matching and semantic space. Based on the conceptual model and the literature study, the complete service matching approach is then provided with four essential steps - semantic space, parameter tree, similarity measures, and WSDL operation matching. The system demonstration that proves the concept proposed in this approach is finally presented. The solution has the potential to facilitate the Internet services mashup.

Trust is widely acknowledged as being important for the efficient and effective operation of business in virtual environments. This is because trust functions like a glue that holds and links virtual agents together as they relate and collaborate remotely. In virtual environments, trust needs to be established swiftly as there is little time to build it gradually in the absence of face-to-face meetings. However, the manner in which trust develops and is maintained is a critical factor in relationships, both physically and virtually. In virtual environments, trust needs to be managed including network connection as well as social aspects of interaction. Maintaining trust in virtual environments is defined as an effort to maximize the benefits of such virtual relationship and to prevent the level of trust from decreasing. In this paper, we undertake a general survey of the current situation of trust maintenance in virtual environments. We review several researches from the perspective of terminology, strategies presented, and types of strategies. We describe the benefits and shortcomings of each strategy, conduct an integrative review of these strategic approaches, and make suggestions for future research.

This paper reports on a study in which developers' cognitive levels were categorised and measured while they mapped a sequence diagram to the related code based on a usage based reading scenario. Results indicate that applying the usage-based reading technique to map a sequence diagram to the underlying code, facilitates a developer to operate at the knowledge and comprehension levels of Bloom's cognitive taxonomy, but does not facilitate sustaining it at the analysis level. The results of this study highlight the need for improved tools and methodologies that aid developers understanding of the system, particularly for those commencing a new project.

Wireless Multimedia Sensor Networks (WMSNs) is comprised of small embedded video motes capable of extracting the surrounding environmental information, locally processing it and then wirelessly transmitting it to parent node or sink. It is comprised of video sensor, digital signal processing unit and digital radio interface. In this paper we have surveyed existing WMSN hardware and communication protocol layer technologies for achieving or fulfilling the objectives of WMSN. We have also listed the various technical challenges posed by this technology while discussing the communication protocol layer technologies. Sensor networking capabilities are urgently required for some of our most important scientific and societal problems like understanding the international carbon budget, monitoring water resources, monitoring vehicle emissions and safeguarding public health. This is a daunting research challenge requiring distributed sensor systems operating in complex environments while providing assurance of reliable and accurate sensing.

Abstract Service‐oriented computing (SOC), Grid computing, and Web2.0 computing have increasingly received momentum in both research and industry. In this paper, we propose an abstract Web‐inclusive distributed computing model (WIDCOM) in order to analyse these three important distributed computing paradigms. We then advance the notion of software in existing Grid services as discussed in open Grid services architecture, which provides software middleware or wrappers for accessing hardware resources towards the notion that the resources provided can be hardware, software, or hybrid hardware/software. It also proposes an approach using the integration of Grid service, semantic Grid, and Web2.0 to overcome some of the limitations of the existing Web services architecture, which relies on having the Web version of the RPC mechanism and thus has difficulty in dealing with massive scale of user participation and communication across the Internet. The new approach produces a novel Grid architecture—GRIDSpace. Copyright © 2008 John Wiley & Sons, Ltd.

This paper aims to present an ontology model of software engineering to represent its knowledge. The fundamental knowledge relating to software engineering is well described in the textbook entitled Software Engineering by Sommerville that is now in its eighth edition (2004) and the white paper, Software Engineering Body of Knowledge (SWEBOK), by the IEEE (203) upon which software engineering ontology is based. This paper gives an analysis of what software engineering ontology is, what it consists of, and what it is used for in the form of usage example scenarios. The usage scenarios presented in this paper highlight the characteristics of the software engineering ontology. The software engineering ontology assists in defining information for the exchange of semantic project information and is used as a communication framework. Its users are software engineers sharing domain knowledge as well as instance knowledge of software engineering.

Self-healing key distribution schemes are particularly useful when there is no network infrastructure or such infrastructure has been destroyed. A self-healing mechanism can allow group users to recover lost session keys and is therefore quite suitable for establishing group keys over an unreliable network, especially for infrastructureless wireless networks, where broadcast messages loss may occur frequently. An efficient threshold self-healing key distribution scheme with favorable properties is proposed in this paper. Firstly, the distance between two broadcasts used to recover the lost one is alterable according to network conditions. This alterable property can be used to shorten the length of the broadcast messages. Secondly, any more than threshold-value users can sponsor a new user to join the group for the subsequent sessions without any interaction with the group manager. Thirdly, the storage overhead of the self-healing key distribution at each group user is a polynomial over a finite field, which will not increase with the number of sessions. In addition, if a smaller group of users up to a threshold-value were revoked, the personal keys for non-revoked users can be reused.

The increasing body of distributed and heterogeneous information and the autonomous, heterogeneous and dynamic nature of information resources are important issues hindering effective and efficient data access, retrieval and knowledge sharing. The importance of ontologies has been recognised within the biomedical domain and work has begun on developing and sharing biomedical ontologies. In this paper, we define ontology and ontology commitments and explain the main characteristics and representations of ontology models. Ontologies are highly expressive knowledge models and as such increase expressiveness and intelligence of a system. We highlight the significance of ontologies in a variety of semi-automatic and automatic tasks, and provide an illustrative example of an ontology-based multi-agent system designed to intelligently retrieve information about human diseases from a number of heterogeneous and dispersed information resources.

Ontologies and controlled vocabularies are being established by many groups to provide roadmaps through the confused mass of data currently being generated from increasingly large-scale experimental biological experiments. The world of protein chemistry is no exception to this rule, with protein ontology (PO) having lead the field by providing a framework in which individual molecules and complexes can be defined by their structure, function and cellular location. PO performs searches across the protein databases using a standard nomenclature consistent to all entries.

The concept of mashup is gaining tremendous popularity and its application can be seen in a large number of domains. Enterprises using and relying upon mashup have improved their mass collaboration and personalization. In order for mashup technology to be widely accepted and widely used, we need a methodology by which can make use of the quality of the input to the mashup process as a governing principle to carry out mashup. This paper reviews the concept of mashup in different domains and proposes a conceptual solution framework for providing quality based mashup process.

In this paper, we describe a XML based profile for modeling the semantics of real time systems. We aim to use Real Time Markup Language (RTML) to provide a comprehensive description of temporal properties for the use in distributed systems communication. RTML is derived from a number of specifications including OMG UML Profile in Schedulability, Performance, and Time. In this paper, we discuss the technique that was used to develop RTML semantic model and the important concepts in RTML.

Software maintenance can consume up to 70% of the effort spent on a software project, with more than half of this devoted to understanding the system. Performing a software inspection is expected to contribute to comprehension of the software. The question is: at what cognition levels do novice developers operate during a checklist-based code inspection followed by a code modification? This paper reports on a pilot study of Bloom's taxonomy levels observed during a checklist-based inspection and while adding new functionality unrelated to the defects detected. Bloom's taxonomy was used to categorise think-aloud data recorded while performing these activities. Results show the checklist-based reading technique facilitates inspectors to function at the highest cognitive level within the taxonomy and indicates that using inspections with novice developers to improve cognition and understanding may assist integrating developers into existing project teams.

It is observed that there are few service evaluation and ranking methodologies currently available in the SOE. In this paper, we propose an innovative service evaluation and ranking strategy, based on the measurement of trustworthiness and reputation of services (or service providers'). CCCI Metrics originally proposed and developed by Chang et al [1] is used to measure the trustworthiness and reputation of e-services. Here we extend the application of CCCI Metrics to the field of service retrieval. A java-based search engine prototype is designed, with the purpose of implementing the trustworthiness and reputation-based service search, evaluation and ranking. Conclusions and future works are drawn in the final section.

Due to the inherent flexibilities in both structure and semantics, XML association rules mining faces few challenges, such as: a more complicated hierarchical data structure and ordered data context. Mining frequent patterns from XML documents can be recast as mining frequent tree structures from a database of XML documents. In this study, we model a database of XML documents as a database of rooted labeled ordered subtrees. In particular, we are mainly concerned with mining frequent induced and embedded ordered subtrees. Our main contributions are as follows. We describe our unique embedding list representation of the tree structure, which enables efficient implementation of our Tree Model Guided ( TMG ) candidate generation. TMG is an optimal, nonredundant enumeration strategy that enumerates all the valid candidates that conform to the structural aspects of the data. We show through a mathematical model and experiments that TMG has better complexity compared to the commonly used join approach. In this article, we propose two algorithms, MB3-Miner and iMB3-Miner. MB3-Miner mines embedded subtrees. iMB3-Miner mines induced and/or embedded subtrees by using the maximum level of embedding constraint . Our experiments with both synthetic and real datasets against two well-known algorithms for mining induced and embedded subtrees, demonstrate the effectiveness and the efficiency of the proposed techniques.

Ontologies are the foundation of the semantic Web (SW) and one of the keys necessary to its success. Conversely, e-Science domains are usually characterized by heterogeneous semistructured data models and formats. In recent years, building ontologies are gaining momentum in the e-science domains to provide explanatory semantics in an agreed, yet shared encodings. Conversely, ontology views hold the promise of; (a) provide a manageable portion of a larger ontology for the localized applications and users, (b) enable precise extraction of sub-ontologies of a larger ontology that commits to the main ontology, (c) enable localized customization and usage of the portion of a larger ontology and (d) enable interoperability between large ontology bases and applications. Therefore, it is interesting to look at ontology views and their desired applications in the context of e-Sciences, as there exists no agreed upon standard, methodology or formalism to specify, define and materialize such ontology views. Thus, in this paper, we elaborate on our own research direction towards proposing a meaningful ontology view formalism and its associated semantics for the e-science domain.

Protein ontology is designed to provide a structured protein data specification for protein data representation. Protein ontology is a standard for representing protein data in a way that helps in defining data integration and data mining models for protein structure and function. In paper we summarize the development of PO that we discussed in previous chapters. A large number of diverse bioinformatics sources are available today. The future of biological sciences promises more data. No individual data source will provide us with answers to queries that we need to ask. Instead knowledge has to be composed from multiple data sources to answer the queries. Even though multiple databases may cover same data their focus might be different. Thus, protein ontology project is an ongoing project with creation of every new protein data source. We also outline here in this paper the future work that we will be doing in protein ontology project.

To ascertain the possible level of risk in a digital business ecosystem interaction, the initiating agent has to determine beforehand the probability of failure, the possible consequences of failure, and the loss of investment probability to its resources while interacting with the other agent. Out of these three constituents, the initiating agent can determine beforehand the probability of failure in interacting with an agent either by considering its past interaction history with it or by soliciting recommendations from other agents. In both cases, it is imperative for the agent who is either considering its past interaction history, or who is communicating a recommendation about the other agent, to know the accurate level of failure in interacting with the other agent. To achieve this, in this paper we propose a methodology by which the initiating agent of the interaction ascertains the level of failure in the interaction, after interacting with an agent.

In this paper we present an overview of the definitions of the terms of trust and reputation from the literature. Trust and reputation have been defined in different ways by the various researchers. As a result of these various definitions of trust and reputation there is a lot of confusion regarding what these terms actually mean. Additionally in the literature there is no work towards collecting all the definitions of trust and reputation. In this paper we discuss and present an overview of the terms of trust and reputation from the literature.

Biomedical knowledge of proteomics domain is represented in the protein ontology, whose instantiations, which are undergoing evolution, need a good management and maintenance system. Protein ontology instantiations signify information about proteins that is shared and has evolved to reflect development in protein ontology project and proteomics domain itself. In this paper we explore the development of a conceptual framework for protein ontology instantiations management by using the concepts of trust and reputation in biomedical domain. The developed and engineered ontology approach is trustworthy and facilitates reliable additions and updates to the protein ontology.

It is well-known that ontology is utilized as an effective methodology to share domain-specific knowledge in multidisciplinary fields. In the field of project management, due to the characteristic of project organizations in which project members are geographically dispersed and from different cultural background, senior management would feel difficulty when they attempt to know about the detailed project completion status from dispersed project groups. Thus, the objective of this paper is to propose an automated project track and trace methodology through the use of ontology technology, to challenge the knowledge sharing issues in project organizations. By means of extending CCCI metrics into the field of project management and introducing a new ontological notation system, we deliver the project track and trace ontology.

Due to technological advancement of the Internet, conducting e-commerce transactions have become a part of our daily lives. In a financial interaction to be carried over the digital business ecosystem domain, it is rational for an agent instigating the interaction to analyse beforehand the possible risk in interacting with any other agent. Doing so would give the instigating agent an idea of direction in which its interaction might head and also help it to make an informed decision of its future course of action with that particular agent. For risk analysis, the instigating agent has to determine beforehand the probability of failure and the possible consequences of failure in interacting with an agent. In this paper, we propose such a methodology by which the instigating agent quantifies the probability of failure beforehand in interacting with an agent according to the demand of its future interaction with it.

The M3RT-based real-time traffic pattern detector proposed identifies the Internet traffic pattern on the fly. Firstly it determines if a time series aggregate is stationary. Secondly it confirms if the aggregate exhibits short-range dependence (SRD) or long-range dependence (LRD). Thirdly it detects if the smooth system operation has suddenly become irregular and chaotic. This detection is achieved by computing the instantaneous value of the Holder exponent that has a (0,1) range to accommodate different degrees of fractality. When the Holder exponent has wandered outside the (0,1) region, fractal breakdown has occurred. The capability of detecting such breakdowns by a real-time application enables it to avoid sudden failure. The Intel's VTune Performance Analyzer indicates the proposed model can be deployed in real time effectively. This feature is of importance to the reliability improvement of Web applications which run on the Internet

Digital ecosystems have recently been introduced into the computer and information societies. Digital ecosystem (DES) is the dynamic and synergetic complex of digital communities consisting of interconnected, interrelated and interdependent digital species (DS) situated in a digital environment (DE) that interact as a functional unit and are linked together through actions, information and transaction flows. DES transpose mechanisms from living organisms like autonomy, viability and self-organisation to arrive at novel knowledge and architectures. The proposed DES embraces a number of different technologies such as ontologies, agent-based and self-organizing systems etc. The synergetic effects of these methodologies results in a more efficient, effective, reliable and secure system. DES is still in its early implementation phase. No clear methodology for digital ecosystem design exists yet. In this paper, we propose a methodological framework that consists of five phases and addresses many different aspects of the DES design. In this methodology, we focus on the key factors associated with the DES design such as roles of different digital components within the DES, organisation and collaboration of the digital components, their individual design along with intelligence and security within the DES. More details are introduced at each step and every sequential step takes the DES to a higher level of elaboration. This methodological framework allows better control over the design process and serves as a navigating tool during DES design.

Web service selection is an essential element in service-oriented computing. How to wisely select appropriate Web services for the benefits of service consumers is a key issue in service discovery. In this paper, we approach QoS-based service selection using a decision making model - the analytic hierarchy process (AHP). In our solution, both subjective and objective criteria are supported by the AHP engine in a context-specific manner. We also provide a flexible Wiki platform to collaboratively form the initial QoS model within a service community. The software prototype is evaluated against the system scalability.

In this article, we introduce trust ontologies. An ontology represents a set of concepts that are commonly shared and agreed to by all parties in a particular domain. Here, we introduce generic and specific trust ontologies. These ontologies include the following: an agent trust ontology and trustworthiness; agents include sellers, service providers, Web sites, brokers, shops, suppliers, buyers, or reviewers. A services trust ontology and trustworthiness assists in measuring the quality of service that agents provide in the service-oriented environment such as sales, orders, track and trace, warehousing, logistics, education, governance, advertising, entertainment, trading, online databases, virtual community services, security, information services, opinions, and e-reviews. A goods or products trust ontology and trustworthiness is useful for measuring the quality of products such as commercial products, information products, entertainment products, or second-hand products. We present a trust ontology that is suitable for all types of agents that exist in the service-oriented environment. As agent trust is measured through the quality of goods and services, we introduce two additional distinct concepts of service trust ontology and product trust ontology. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 519–545, 2007.

This article introduces a new transaction protocol using mobile agents in electronic commerce. The authors first propose a new model for transactions in electronic commerce, mutual authenticated transactions using mobile agents. They then design a new protocol by this model. Furthermore, the authors analyse the new protocol in terms of authentication, construction, and privacy. The aim of the protocol is to guarantee that the customer is committed to the server, and the server is committed to the customer. At the same time, the privacy of the customer is protected.

Many of the current issues with information privacy have been the result of inadequate consideration for privacy during the planning, design, and implementation of information systems and communication networks. The area of quantum computation is still in its infancy, and a truly functional quantum computer has not been implemented. However, it is anticipated that within the next decade it may be feasible. This presents a unique opportunity to give due consideration to information privacy in the realm of future quantum computational devices and environments while they are still in their infancy. This article provides an overview of the key information privacy issues that we feel may arise with the evolution and realization of quantum computation. Additionally we propose an integrated approach of technical, legal, and social elements to address these issues.

Trust and Reputation are vital components for trusted e-business. In the literature however there has been no effort in proposing ontology for trust. The trusted agent in service oriented environment may trust a software agent or human agent or a service or product. Based on this distinction, trust ontology could be proposed for different domains. The trust ontology for the individual domains is proposed and discussed.

Trust and Reputation are vital components for trusted e-business. In this paper, we propose a definition of trust relationship. Additionally we discuss in depth about the concept of trust relationship. A definition for reputation relationship is proposed in this paper. Three inner relationships with in the reputation relationship are detailed and discussed. © 2006 IEEE.

Trust and Reputation are vital components for trusted e-business. In this paper, we propose a definition of trust relationship. Additionally we discuss in depth the concept of trust relationship. A definition for reputation relationship is proposed in this paper. From the analysis of reputation relationship we find that the reputation relationship is a composite relationship and is composed of three inner relationships. We propose the three inner relationships and define them. We then propose the characteristics of the inner relationships within the reputation relationship.

The trusting peer in order to determine the likelihood of the loss in its resources might analyze the Risk before engaging in an interaction with any trusted peer. This likelihood of the loss in the resources is termed as Risk in the interaction. Risk analysis is important in e-commerce transactions because of the vast literature that argues that the decision to buy is based on the Risk-adjusted cost-benefit analysis. If the trusting peer can determine the future Riskiness value or reputation of a trusted peer for the time period of its interaction, before engaging in an activity with it, then it can ease its decision making process of whether to interact with the trusted peer or not. In this paper we present such a novel method which predicts the dynamic nature of Risk and determines the future Riskiness value of the trusted peer, before the interaction starts, thus helping the trusting peer considerably in making its decision. © 2006 IEEE.

Undeniable signatures are the digital signatures that should be verified with the help of the signer. A signer may disavow a genuine document, if the signature is only verifiable with the aid of the signer under the condition that the signer is not honest. Undeniable signatures solve this problem by adding a new feature called the disavowal protocol in addition to the normal components of signature and verification. Disavowal protocol is able to prevent a dishonest signer from disavowing a valid signature. In some situations, an undeniable signature should be converted into a normal digital signature in order that the signature can be universally verified. Blind signatures the digital signatures that help a user to get a signature on a message without revealing the content of the message to a signer. For the blind signatures, if the signer is able to make an agreement with the user, then the underlying signer may include some common information that is known to the user, then such signatures are partially blind signatures. Convertible undeniable partially blind signatures are of the features of undeniable signatures, blind signatures, convertible undeniable signatures, and partially blind signatures. Recently, a convertible undeniable partially blind signature scheme was presented. In this paper, we first analyze a security flaw of the convertible undeniable partially blind signature scheme. To address the security flaw, we present an improvement on the disavowal protocol. The improved scheme can prevent the signer from either proving that a given valid signature as invalid, or cheating the verifier

As there is a lack of central management in an e-commerce interaction carried out based on peer-to-peer architecture, it is obvious for the trusting peer to analyze the risk beforehand that could be involved in dealing with a trusted peer in these types of interactions. Another characteristic of peer-to-peer architecture interactions is that the trusting peer might have to choose a peer to interact with, from a set of possible trusted peers. It can ease its decision making process of choosing a peer to interact with by analyzing the risk that could be involved in dealing with each of the possible trusted peers. In this paper we highlight and propose a solution to this problem by which the trusting peer can decide with which peer to interact with after analyzing the risk that could be associated in dealing with each of them

Biomedical Ontologies are huge. It is not possible for any one person to manage and engineer a complete ontology. They would need the help of Research Assistants and other people to develop and maintain the ontology. In the process of developing and maintaining the ontology the Research Assistants may enter incorrect data, resulting in low quality of the ontology. In this paper we will propose a conceptual framework to solve these ontology management and ontology development issues. There can be N assistants entering data into the ontology. All the data entered initially is stored in an intermediate ontology. The administrator of the ontology has a set of rules, which makes a checklist that checks and validates the data in intermediate ontology for correctness according to the ontology schema. We use the Case Study of Protein Ontology for this proposed approach to develop interfaces for assistants and administrators. The proposed approach can easily be extended to other biomedical ontologies just by tweaking the administrator rule set according to the ontology.

Advances in proteomics and protein expression techniques have lead to the elucidation of large amounts of protein data. Various data mining algorithms and mathematical models provide methods for analyzing this data; however, there are two issues that need to be addressed: (1) the need for standards for defining protein data description and exchange formats so they can be exchanged across the World Wide Web, and also read into data mining software in a consistent format and (2) eliminating errors which arise with the data integration methodologies for complex queries. Protein Ontology is designed to meet these needs by providing a structured protein data specification for Protein Data Representation. Protein Ontology is a standard for representing protein data in a way that helps in defining data integration and data mining models for Protein Structure and Function. In this paper we summarize the structure of Protein Ontology we developed earlier, its current applications to various protein families, and its future development.

The benefits of Service Oriented Architectures (SOAs) start to be recognized and implemented across distributed enterprise businesses. As SOAs promise to accomplish more dynamic and collaborative e-business scenarios, we need to ensure that critical factors such as trust, credibility and quality of service (QoS) are consistently and efficiently measured in such unsupervised environments. We propose a fuzzy logic-based model for the review of service fulfilment after a business interaction and demonstrate its functionalities in an exemplary application. The outcome of our model can then be used to adjust credibility records of third party agents which delivered opinions, to update trustworthiness values in the business partner, or to communicate the trustworthiness of the business partner to interested peer agents.

Due to the increasing dependency on self-describing, schema-based, semi-structured data (e.g. XML), there exists a need to model, design and manipulate semi-structured data and the associated semantics at a higher level of abstraction than at the instance or document level. In this paper, we extend our research and propose to visually model (at the conceptual level) and transform dynamic properties of views in the Layered View Model (LVM) using the eXtensible Semantic (XSemantic) net notation. First, we present the modeling notation and then discuss the declarative transformation to map the dynamic XML view properties to XML query expressions, namely XQuery.

This paper presents an overview of the real time markup language (RTML). RTML is a XML profile which provides the syntactic representation for describing the semantics of real time data for exchange over distributed networked real time systems. For the basis of interoperability, this profile is described in the XML schema language. This paper describes the background of this work and shows how the vocabularies are developed, and how it derives the extensibility of XML schema in aiding the definition of data in real time systems in order to achieve the goal of interoperability.

Software engineering project information is frequently evolving and queried to reflect project development changes in the software requirements or in the design process, to incorporate additional functionality to systems or to allow incremental improvement and the like. Therefore, the project information needs enhancement to ease up-to-date ontological information and to ease communication. Ontologies are widely used for capturing and organising knowledge of a particular domain of interest. We propose the use of software engineering ontology instantiations and enrichment to capture the software engineering project information

Purpose Information Privacy is becoming an increasingly important field of research with many new definitions and terminologies. Along similar rates of increase are the use, uptake and expansion of collaborative environments (CEs). There is a need for a better understanding and classification of information privacy concepts and terms. The purpose of this paper is to provide a taxonomy of information privacy in CEs. The knowledge provided from an information privacy taxonomy can be used to formulate better information privacy policies, practices, and privacy enhancing technologies. Design/methodology/approach Through the hierarchical classification and categorization of information privacy concepts and principles an organized representation of these components has been produced. Each area was well surveyed and researched and then classified into a number of sub-categories according to their nature and relevance. Findings A taxonomy was successfully developed with the identification of three high level dimensions of information privacy. Within each dimensional view a further three sub-classifications were proposed each with their own unique nature. Originality/value This paper provides an Information Privacy taxonomy for CEs, the first of its kind to be proposed. A number of new Information privacy terms are defined that make up the categorization and classification of information privacy concepts and components.

Usability of software should measure both user preference and user performance. The notion of usability involves several dimensions. These dimensions include: system feedback, consistency, error prevention, performance/efficiency, user like/dislike, and error recovery. Each of these dimensions are characterized by fuzzy aspects and linguistic terms. This paper develops a model for each of the dimensions using fuzzy-set theory. It then uses the Takagi-Sugeno fuzzy-inference approach for developing an overall measure of usability. Results are presented for several different user interfaces.

The user interface for computer applications is typically hard coded and offers minimal flexibility for user customisation. In this paper we list and discuss several requirements for application user interfaces that offer widespread application accessibility, access across international boundaries, and that support user interface individualisation by normal users (without the need for specific software customization by developers). We review related works in XML based user interface deployment and identify shortcomings, and present a solution that we name the Web service based adaptable user interface (WAUI). The major features of the WAUI are; the decoupling of the traditional user interface from both the execution platform and the rest of the application layers by the use of Web services, and providing for an automated user interface adaptation capability based on; the user's selected cultural and internationalization options, the user's preferences for alternative visual display objects, and the preferences that a user defines for modifying the function and layout of application forms and display objects.

In this paper we propose software engineering subontology. We called it application-specific ontology, for specific software development. It enables remote team members browsing, searching, sharing, and authoring ontological data under the distributed software engineering projects environment. We transform explicit meaningful human knowledge into application-specific ontology, where knowledge structures and semantics are linked, and we go through a formal hand-shaking agreement establishing process before the semantic contents are updated in ontology repositories. The application-specific ontology is used for communication over project agreement to facilitate better, highly consistent communications and formalized domain knowledge sharing. We assume that object-oriented development is deployed in the distributed projects. The knowledge of object-oriented development formed in the application-specific ontology clarifies the objectoriented development concepts in a machine understandable form. Software agent, for example, can be utilised to extract information.

The growing development of Web based trust and reputation systems in the 21st century will have powerful social and economic impact on all business entities, and will make transparent the quality assessment and customer assurance realities in the distributed Web based service oriented environments. The Web based trust and reputation systems will be the foundation for Web intelligence in the future. Trust and reputation systems help capture business intelligence through establishing customer relationships, learning consumer behavior, capturing market reaction on products and services, disseminating customer feedback, buyers' opinions and end-user recommendations, and revealing dishonest services, unfair trading, biased assessment, discriminatory actions, fraudulent behaviors, and untrue advertising. The continuing development of these technologies will help in the improvement of professional business behavior, sales, reputation of sellers, providers, products and services. However there has been no effort in defining ontology for reputation. In this paper we attempt to define ontology for reputation.

Transportation and warehousing logistics are activities that require strong information systems and computer support. This requirement has grown with the advent of e-commerce. Companies such as FedEx and UPS now allow their customers to track and monitor the fulfillment of their requested services on the Internet. In order for such a system to be effective, the goods need to be handled by the one corporation, with an integrated system. This is rare in the case of small to medium sized enterprise (SME). With the advent of business to business (B2B), and partner to partner (P2P) e-commerce, there has been an increasing tendency for SMEs to set up consortia that represent several players in a given field in order to contend with larger competitors. This paper deals with the concept of an extended logistics enterprise and explores the software engineering issues underlying the development of such complex systems.

The eXtensible Markup Language (XML) is fast emerging as the dominant standard for describing and interchanging data among various systems and databases on the Internet. It offers the Document Type Definition (DTD) as a formalism for defining the syntax and structure of XML documents. The XML Schema definition language, as a replacement for the DTD, provides more rich facilities for defining and constraining the content of XML documents. However, it does not concentrate on the semantics that underlies these documents, representing a logical data model rather than a conceptual model. To enable efficient business application development in large-scale electronic commerce environments, it is necessary to describe and model real-world data semantics and their complex interrelationships. In this article, we describe a design methodology for XML documents. The aim is to enforce XML conceptual modeling power and bridge the gap between software development and XML document structures. The proposed methodology is comprised of two design levels: the semantic level and the schema level . The first level is based on a semantic network, which provides semantic modeling of XML through four major components: a set of atomic and complex nodes, representing real-world objects; a set of directed edges, representing semantic relationships between the objects; a set of labels denoting different types of semantic relationships, including aggregation, generalization, association , and of-property relationships; and finally a set of constraints defined over nodes and edges to constrain semantic relationships and object domains. The other level of the proposed methodology is concerned with detailed XML schema design, including element/attribute declarations and simple/complex type definitions . The mapping between the two design levels is proposed to transform the XML semantic model into the XML Schema, based on which XML documents can be systematically created, managed, and validated.

Activity diagrams are a recognized form of modelling real time systems and have been included in the list of UML techniques for modelling the dynamic aspects of object oriented systems. In this paper, we explain how workflow techniques can be used for developing models of larger chunks of systems. These chunks are expressed through the use of worklets. This can then be used as the basis of modelling systems where timeliness is of importance. However, this requires extending workflow ideas to incorporate flexibility, handling of exceptions and adaptability. Extensions of the activity diagrams are then proposed for expressing the models obtained from such workflow techniques. This will allow evolution of real time systems development towards a component based approach.

With the increasing popularity of object-relational technology, it is becoming important to have a methodology which allows designers to exploit the great modelling power of object-oriented conceptual models (OOCMs) and yet which still facilitates implementation on relational database systems. This paper presents a practical solution for the implementation of different types of object-oriented association relationships, which include a wide range of collection types (i.e. sets, lists, arrays and bags), into relational database tables. The implementation strategies raise a number of constraints relating to data integrity in the database system. These constraints are associated with (i) normalisation of the resulting relational tables, and (ii) data integrity after insertion/deletion. In order to ensure completeness of the strategies, some techniques for the implementation of inverse traversal in association relationships are also provided. An example is used throughout this paper to demonstrate and evaluate the proposed method.

The design of the user interface (UI) involves: a) logical design of the UI; and b) perceptual design of the UI. The logical design of a user interface includes both static or data related and dynamic or navigational aspects. The static aspects were discussed previously (E.J. Chang and T.S. Dillon, 1997). An important part of the static design is the determination of abstract user interface (AUI) objects. These abstract interface objects contain all of the information related to carrying out: (i) entry and display of information; (ii) actions that need to be taken by the user to move to another AUI object or window; (iii) actions to initiate or stop an action within the system. They do not however, contain information on the set of preconditions that must hold before a particular action under (ii) or (iii) above can be taken. Nor do they contain information on the set of post conditions that apply after the action is taken. These preconditions and post conditions, when chained together, specify the sequencing of events between the AUI objects. We define the Flow of Interaction Nets (FIN) which provide information related to this sequencing. These nets define the Flow of Interaction between the user and the system.