Cloud services have been adopted by more and more consumers and different types of businesses. An intrinsically difficult problem faced by service consumers and businesses is that no standard way to evaluate and compare cloud services' trustworthiness, while trust has already become a critical factor for service and service provider selection. In this paper, we propose a trustworthiness evaluation and comparison framework to help make customized selection decisions based on trustworthiness. This framework utilizes fuzzy processing and neural network to handle subjectivity and inaccuracy, and customized recommendation. A feedback learning mechanism is also incorporated to make the entire framework be adaptive to users' preferences. The framework is implemented as prototype system to evaluate and recommend different types of cloud services. Experiments on different types of services and different types of trustworthiness prove the effectiveness and efficiency of the proposed framework.

Cloud service systems need an efficient and flexible platform to offer services and computational resources to users. However, emergent event detection and prediction for platform reliability management is still an unsolved problem for most cloud service providers, especially for virtualized platforms. Hardware failure, software errors, outside attacks, and mis-actions of virtual machines make cloud platforms unstable and unreliable. In order to avoid critical events affecting reliability, resources, applications, and services can be rescheduled to get around predicted failures and mitigate potential impacts. In a cloud platform, different layers of service execution may generate different types of system events. Events from different layers can affect a system's stability together. Thus, event pattern detection and prediction are especially important for reliability and stability management. In this paper, we propose a framework to detect and predict system critical event patterns from different service types and execution layers using a reversed pattern tree augmented mechanism, so that detection and prediction can speed up. Meanwhile, wavelet neural network is also used to control the balance between prediction accuracy and speed, so that system reliability and stability can be improved. The effectiveness of this framework is tested and confirmed in a real cloud environment.

Web service recommendation systems can help service users to locate the right service from the large number of available web services. Avoiding recommending dishonest or unsatisfactory services is a fundamental research problem in the design of web service recommendation systems. Reputation of web services is a widely-employed metric that determines whether the service should be recommended to a user. The service reputation score is usually calculated using feedback ratings provided by users. Although the reputation measurement of web service has been studied in the recent literature, existing malicious and subjective user feedback ratings often lead to a bias that degrades the performance of the service recommendation system. In this paper, we propose a novel reputation measurement approach for web service recommendations. We first detect malicious feedback ratings by adopting the cumulative sum control chart, and then we reduce the effect of subjective user feedback preferences employing the Pearson Correlation Coefficient. Moreover, in order to defend malicious feedback ratings, we propose a malicious feedback rating prevention scheme employing Bloom filtering to enhance the recommendation performance. Extensive experiments are conducted by employing a real feedback rating data set with 1.5 million web service invocation records. The experimental results show that our proposed measurement approach can reduce the deviation of the reputation measurement and enhance the success ratio of the web service recommendation.

The cloud computing platform provides an efficient and flexible way to offer services and computation facilities to users. However, reliability in the cloud is an important factor to measure the performance of a virtualized cloud computing platform. System failure, software failure, outside attacks, and mis-actions of virtual machines make the cloud computing platform unstable and unreliable. In order to avoid critical events affect reliability, resources, applications, and services can be scheduled around predicted failure and limit the impact. In the cloud computing platform, different virtual machines may generate number of system events. Events from different virtual machines can affect system stability together. Such mechanisms are especially important for cloud computing environment. In this paper, we propose a framework to recognize and predict system critical events that come from different virtual machines to increase system stability of cloud computing environment.

Cloud computing provides many benefits for individuals and enterprises by offering a range of computing services. The service dynamism, elasticity, economy and choices are too attractive to ignore. At the meantime, cloud computing has opened up a new frontier of challenges by introducing trust scenario. The Trustworthiness Evaluation of cloud Services is a paramount concern. In this paper, we present a framework to quantitatively measure and rank the trustworthiness of cloud services. In particular, we address the fundamental understanding of trustworthiness, quantitative trustworthiness metrics, unified scale of trust factors, trust factors categorization, trust coordinate and multi-criteria analysis for trustworthiness decision making. Our comprehensive framework of trustworthiness evaluation contains five basic building blocks. The preprocessing block query and calculate the existent trustworthiness record. Then the trust factors are collected, if there was no match record found. The trust factor management block categorize the trust factors and convert them by using unified scale. The trust factor processing block is for weighting and positioning of trust factors. The trustworthiness decision making block provide calculation of cloud service trustworthiness, and the results are recorded in our trustworthiness record block. The proposed trustworthiness measurement framework is employed in several experiments by using existing trust dataset. The analysis based on the experiment result indicates our trustworthiness evaluation is accurate and flexible.

In this paper, we present a framework for complex scenarios recognition with crowded walkers. This study aims to develop an alternative surveillance system to traditional video camera and visual sensor based systems. Instead of utilizing visual devices in traditional surveillance systems, our crowded scene analysis is based on PIR (Pyroelectric Infrared) sensor networks with intelligent algorithms for context pattern extraction and analysis. Specifically, we will propose two new ideas to handle the crowded scenes: (1) Use hierarchical Bayesian NMF (Non-negative Matrix Factorization) algorithm to automatically identify the basic pattern basis, which will be used for accurate scenario recognition, (2) Use a tree-based structure to organize all basic features for fast object recognition. The experimental results valid the efficiency of the proposed two schemes on crowded scenario recognition with low-cost, non-visual system. The results also demonstrate that our framework is appropriate to be implemented in a wireless sensor based monitoring system under severe circumstances.

In collaborative workspace, collaborations are constrained by different requirements between different participants. Since policy-based management can be used to simplify collaboration management, administrators and users can use policies to define control rules and configurations of collaborative w

Mobile social networks give online social networking sites the abilities to extend their services to mobile device users. Smart phones and tablets allow users to interact with others when they are moving. Policy-based management simplifies the management of interaction functionalities by establishing policies to control various activities involved in these functionalities. To detect and resolve potential dynamic conflicts between the rules and configurations from different administrative domains, a knowledge-based policy analysis framework is proposed in this paper. It incorporates relationships between different elements in policy rules into temporal logic using a knowledge extension, which makes dynamic policy conflict analysis more accurate. A prototype system for mobile social networks is implemented to illustrate the capability of this framework.

Policy-based management can simplify web service management by establishing policies to control various activities involved in service governance and provision. Administrators and users use policies to define control rules and restrictions, and to configure application environments. When collaboration is necessary between web services for a specific task, various management requirements from individual services may have conflicts. Some conflicts are static. Some conflicts are dynamic, which are difficult to detect and resolve. The situation is even worse when the collaboration is a one-time event. To detect and resolve potential dynamic conflicts between web services in a collaborative setting, especially between web services from different administrative domains, a semantic temporal logic is proposed and used in this paper to analyze dynamic policy conflicts. An implementation and resultant experiments are also discussed.

Web services provide a standard interaction interface for network-based services. With so many diverse web services available over the Internet, services can be composed together and delivered to users as a package. The way to combine services is still an open problem, especially considering users' preferences. Users always have vague opinions on these preferences when they choose component services. In this paper, we propose a user-preference-based selection engine to compose services, which allows users to define non-quantifiable factors and policies to represent their preferences. Then, the engine automatically composes web services into a package following these policies by use fuzzy logic. The engine ensures the whole package has the most satisfaction.

This paper proposes an enforcement architecture and develop a simulation framework for cross-domain policy enforcement. The entire simulation environment is used to solve the problem of enforcing policies across domain boundaries when permanent or temporary collaborations have to span over multiple

In e-commerce applications, the magnitude of products and the diversity of venders cause confusion and difficulty for the common consumer to choose the right product from a trustworthy vender. Although people have recognized the importance of feedback and reputation for the trustworthiness of individual venders and products, they still have difficulty when they have to make a shopping decision from a massive number of options. This paper introduces fuzzy logic into rule definition for users' preferences and designs a novel agent-based decision system using fuzzy rules. This system can help users to find the right product recommendation from a trustworthy vender following users' own preferences.

Policy-based methods simplify the management of cross-domain collaborations by establishing policies to control various cross-domain activities involved in those collaborations. Administrators and users from participant domains can use policies to define control rules and restrictions, and to config

Cross-domain collaboration between enterprises needs a trusted execution environment. Policy-based management is a promising and convenient way to construct and manage such an environment. Since management of security and trust policies from collaborating domains has to handle different policies and

In policy-based management, the gap between policy definition and enforcement mechanisms needs an architectural innovation to fill. Policy-based trust management has this gap too. Enforcement of policies for federation activities, especially trust policies among Web-service-based systems, requires a dynamic and flexible architecture to accommodate different trust models and different domains. Meanwhile, the choice of high-level policy languages cannot have an exact match to low-level enforcement mechanisms in network services or operating systems. An intermediate-level semantic translation architecture is proposed in this paper to bridge the gap between high-level policy languages used directly by humans and low-level mechanisms offered by machines. The merits of this architecture include: users can choose their high-level policy languages with the most usability they want; the system administrator can introduce a new core mathematical or logical model when it is more appropriate for system controls; the semantic translation in the intermediate-level is flexible.

In an e-commerce environment, the magnitude of products and the diversity of venders cause confusion and difficulty to choose the right product from a trustworthy vender. Although people have recognized the importance of feedbacks and reputations for the trustworthiness of individual venders and products, they remain uncertain when they have to define and enforce their own rules to use these different types of information. This paper introduces fuzzy logic into policy definition and enforcement in personalized recommendation for shopping decisions. Applications of this system into different e-commerce environments such as e-shopping and e-auction sites show that this novel tool can provide a convenient and accurate recommendation platform for common shoppers in the e-commerce environment.

In e-commerce applications, the magnitude of products and the diversity of venders cause confusion and difficulty for common consumers to choose the right product from a trustworthy vender. Although people have recognized the importance of feedbacks and reputations for the trustworthiness of individual venders and products, they still have difficulties when they have to make a shopping decision from a huge number of choices. This paper introduces fuzzy logic into rule definition for preferences of venders and price for products, and designs a novel agent-based decision system using fuzzy rules and reasoning mechanisms to find the right product from a trustworthy vender according to users' preferences.

In federated systems, trust management is critical for information sharing and online collaboration. Security tokens provide a way to convey and exchange trust information for security and privacy protection. Although several communication protocols have mechanisms to exchange security tokens, users may still encounter difficulties when they have to handle security tokens across heterogeneous platforms and security domains. Semantic gaps and incompatibilities are major barriers for trust information exchange in federated trust management. This paper introduces a hybrid approach with intermediary- and query-based mechanisms to resolve semantic gaps and incompatibilities for different types of trust information exchanged by security tokens, and then proposes different exchange models for different types of information. This paper also provides a comprehensive framework to exchange security tokens across security domains with suitable approaches and exchange models. The application of this framework in a healthcare environment provides a new method to interoperate trust information for security- and privacy-critical applications.

In federated networks, trust management is critical to information sharing and online collaboration. Security tokens provide a way to convey and exchange trust-related information for security and privacy purposes. Common users encounter difficulties when they have to handle security tokens across heterogeneous domains. Semantic gaps and incompatibilities are major barriers for trust-related information exchange in federated trust management. This paper uses intermediary-based, query-based and hybrid approaches to resolve these issues for different types of information in security tokens, and proposes three exchange models accordingly. This paper also provides a comprehensive framework using Web services to exchange security tokens across security domains with suitable approaches and exchange models.

In federated and pervasive networks, trust management has become a cornerstone for information security and privacy. Although people have recognized the importance of privacy and security for their personal information, they remain uncertain when they have to define and enforce their own access control rules or have to handle indirect information. Indirect information and subjective judgment are the major sources of uncertainty in federated trust management. This paper introduces fuzzy logic into the definition and evaluation of trust, and then provides a formal representation of fuzzy rules. It also offers a set of derivation rules for analyzing and reasoning among fuzzy rules in order to enforce these rules with a certain level of uncertainty. Application of this model to a healthcare environment with pervasive computing devices across trust domains provides a new method to handle uncertainty in trust management for federated and pervasive networks

With the development of Web technology and distributed systems, online collaborations are becoming more common and more demanding. Web services now provide standard mechanisms to enable online interactions. Yet security, privacy and trust-related protection mechanisms for Web services need additional development. In an interconnected network environment, physical connections with proper security protections are required for bridging two autonomous networks. Likewise, collaborating organizations need mechanisms for bridging extant relationships among cooperating parties that provide proper protection for privacy and trust. A trust establishment mechanism for Web services must therefore ensure privacy and owner control at all times due to the subjectivity of trust relationships. This paper describes an indirect trust establishment mechanism to bridge and build new trust relationships from extant trust relationships providing privacy protection and owner control simultaneously

With the emergence of an effective infrastructure supporting Grid Computing and Web Services, service-oriented computing has been growing over the last few years, and service-oriented architectures are becoming an important computing paradigm. When different trust domains control different component services, trust management plays a critical role to smooth the collaboration among component services. The federation of these component services makes new demands for managing trust-related behavior. Although many extant trust management systems deal with intradomain trust behaviors, there is a growing need for effective strategies for managing inter-domain behaviors. In this paper we explore requirements for a federated trust management system. The purpose of this paper is not to suggest a single type of system covering all necessary features; instead, its purpose is to initiate a discussion of the requirements arising from inter-domain federation, to offer a context in which to evaluate current and future solutions, and to encourage the development of proper models and systems for federated trust management. Our discussion addresses issues arising from trust representation, trust exchange, trust establishment, trust enforcement, and trust storage.

1. With the development of web technology and distributed systems, online collaborations are becoming more common and more demanding. These collaborations require online business trust relationships among collaborating organizations. Online business trust relationships can protect the trust, integrity, and privacy of shared resources, which are the foundation for online business. Web services provide standard mechanisms to enable online interactions and further online collaborations. Yet security, privacy and trust-related protection mechanisms for web services need additional development. In an interconnected network environment, bridging extant business relationships to extend the business circle is a convenient and tempting way. Physical connections with proper privacy and security protections are required for bridging two autonomous organizations. Likewise, collaborating organizations need proper protection mechanisms for bridging extant business trust relationships among cooperating parties. These protection mechanisms must therefore ensure privacy and owner control in the entire process of bridging business trust relationships due to the subjectivity of the relationships. This paper describes an indirect trust establishment mechanism using web service enhancements to bridge and build new online business trust relationships from extant business trust relationships providing privacy protection and owner control simultaneously.

The lack of effective trust establishment mechanisms for Web services impedes the deployment of trust models for online services. One important issue is the lack of privacy protection in trust establishment. Current Web service technology encourages a client to reveal all its attributes in a standard credential to the service provider for trust establishment. We propose a mechanism whereby the client formulates a single trust primitive by associating a subset of required attributes in a standard credential to negotiate a trust relationship. Client privacy is preserved because only those required attributes are revealed. After negotiation, a trust group element with dynamic validation is used to represent this trust relationship.

The MPEG-4 standard consists of object based coding schemes for multimedia and enables content-based manipulation. An approach based on information fusion, which can be used for the detection and location of video objects (people) is proposed in this paper. The method efficiently integrates color, edge and motion information of video streams. The HSV space provides a better use of the color information than that in the traditional RGB space. Using edge extracted from the motion region for contour adaptation provides an original method to eliminate the contour error. The approach integrating various characteristic features of video streams, when applied in the context of video surveillance and background replacement, performs real-time video object detection and location on a PC.

The MPEG-4 video coding standard consists of object based coding schemes for multimedia and enables content based functionalities. Video objects in still pictures or video sequences should be first identified before the encoding process starts. An algorithm based on information fusion, which can be used for the extraction of foreground objects in video streams in real time is proposed in this paper. The method efficiently integrates image and motion information of video streams. The thresholding technique operated in the HSV space provides a better use of the color information than that in the traditional RGB space. Using enhanced boundary extracted from the motion region for contour adaptation offers an original method to refine the contour.