The serverless Function-as-a-Service (FaaS) paradigm offers a fine granularity for the pay-per-use billing model, where users are charged based on the actual function execution time and do not have to pay for idle resources. Thereby, FaaS in a serverless environment brings the promise that it completely abstracts infrastructure management. This allows the developers to focus solely on application development. On the other hand, the serverless applications, being deployed as a dense web of FaaS artifacts, increase the attack surface. This makes the FaaS paradigm susceptible to financial exhaustion attacks, also known as Denial of Wallet (DoW), where the attacker attempts to inflate the usage bill by illegitimate escalation of resource consumption. This paper proposes a robust detection method for DoW attacks on the serverless platform using the Neural Ordinary Differential Equation (ODE) with a Liquid Time Constant (LTC). The experiments, conducted on a benchmark dataset, represent real-world attack scenarios, compared with baseline methods. The proposed method outperforms the baselines for multiple evaluation metrics, proving its effectiveness in precision-critical scenarios.

Unstructured (or, semi-structured) natural language is mostly used to capture the requirement specifications both for legacy software systems and for modern day software systems. The adoption of a formal approach to the specification of the requirements, using goal models, enables rigorous and formal inspections while analyzing the requirements for satisfiability, consistency, completeness, conflicts and ambiguities. However, such a formal approach is often considered burdening for the analysts’ activity as it requires additional skills, and is therefore, discarded a priori. This works aims to bridge the gap between natural language requirement specifications and efficient goal model analysis techniques. We propose a framework that uses extensive natural language processing techniques to transform a set of unstructured natural language requirement specifications to the corresponding goal model. We combine techniques such as parts-of-speech tagging, dependency parsing, contextual and synonymy vector generation with the FiBER transformer model. An extensive unbiased crowd-sourced evaluation of the proposed framework has been performed, showing an acceptability rate (total and partial combined) of 95%. Time and space analyses of our framework also demonstrate the scalability of the proposed solution.

Abstract In autonomous and robotic systems, the functional requirements (FRs) and non‐functional requirements (NFRs) are gathered from multiple stakeholders. The different stakeholder requirements are associated with different components of the robotic system and with the contexts in which the system may operate. This aggregation of requirements from different sources (multiple stakeholders) often results in inconsistent or conflicting sets of requirements. Conflicts among NFRs for robotic systems heavily depend on features of actual execution contexts. It is essential to analyze the inconsistencies and conflicts among the requirements in the early planning phase to design the robotic systems in a systematic manner. In this work, we design and experimentally evaluate a framework, called SCARS, providing: (a) a domain‐specific language extending the ROS2 Domain Specific Language (DSL) concepts by considering the different environmental contexts in which the system has to operate, (b) support to analyze their impact on NFRs, and (c) the computation of the optimal degree of NFR satisfaction that can be achieved within different system configurations. The effectiveness of SCARS has been validated on the iRobot Create3 robot using Gazebo simulation.

Named entity recognition (NER) is a natural language processing task that has been used in Requirements Engineering for the identification of entities such as actors, actions, operators, resources, events, GUI elements, hardware, APIs, and others. NER might be particularly useful for extracting key information from Software Requirements Specification documents, which provide a blueprint for software development. However, a common challenge in this domain is the lack of annotated data. In this article, we propose and analyze two zero-shot approaches for NER in the requirements engineering domain. These are found to be particularly effective in situations where labeled data is scarce or non-existent. The first approach is a template-based zero-shot learning mechanism that uses the prompt engineering approach and achieves 93% accuracy according to our experimental results. The second solution takes an orthogonal approach by transforming the entity recognition problem into a question-answering task which results in 98% accuracy. Both zero-shot NER approaches introduced in this work perform better than the existing state-of-the-art solutions in the requirements engineering domain.

Abstract In the design of autonomous systems, it is important to consider the preferences of the interested parties to improve the user experience. These preferences are often associated with the contexts in which each system is likely to operate. The operational behavior of a system must also meet various non-functional requirements (NFRs), which can present different levels of conflict depending on the operational context. This work aims to model correlations between the individual contexts and the consequent conflicts between NFRs. The proposed approach is based on analyzing the system event logs, tracing them back to the leaf elements at the specification level and providing a contextual explanation of the system’s behavior. The traced contexts and NFR conflicts are then mined to produce Context-Context and Context-NFR conflict sequential rules. The proposed Contextual Explainability (ConE) framework uses BERT-based pre-trained language models and sequential rule mining libraries for deriving the above correlations. Extensive evaluations are performed to compare the existing state-of-the-art approaches. The best-fit solutions are chosen to integrate within the ConE framework. Based on experiments, an accuracy of 80%, a precision of 90%, a recall of 97%, and an F1-score of 88% are recorded for the ConE framework on the sequential rules that were mined.

An emerging feature of mobile application software is the need to quickly produce new versions to solve problems that emerged in previous versions. This helps adapt to changing user needs and preferences. In a continuous software development process, the user reviews collected by the apps themselves can play a crucial role to detect which components need to be reworked. This paper proposes a novel framework that enables software companies to drive their technology value stream based on the feedback (or reviews) provided by the end-users of an application. The proposed end-to-end framework exploits different Natural Language Processing (NLP) tasks to best understand the needs and goals of the end users. We also provide a thorough and in-depth analysis of the framework, the performance of each of the modules, and the overall contribution in driving the technology value stream. An analysis of reviews with sixteen popular Android Play Store applications from various genres over a long period of time provides encouraging evidence of the effectiveness of the proposed approach.

Requirement prioritization is an inherently important step in the DevOps framework. Unfortunately, the prioritization process often disregards the non-functional requirements and the possible conflicts among them. This implies that unresolved dependencies and conflicts would be identified at integration time only, which may lead to major refactoring issues. We introduce CARO a new tool that generates an ordering among the requirements based on conflicts and dependencies among the requirements. The tool provides a quantitative risk evaluation framework along with risk mitigation strategies based on conflicts and dependencies among the requirements.

Leveraging the benefits of service computing technologies for Internet of Things (IoT) can help in rapid system development, composition and deployment. But due to the massive scale, computational and communication constraints, existing software service models cannot be directly applied for IoT based systems. Service discovery and composition mechanism need to be decentralized unlike majority of other service models. Moreover, IoT services' interfaces require to be light weight and able to expose the device profile for seamless discovery onto the IoT based system infrastructure. In addition to this, the "things" data should be associated with its present context. To address these issues, this paper proposes a formal model for IoT services. The service model includes the physical property of "things" and exposes it to the user. It also associates the context with the "things" output, which in turn helps in extracting relevant information from the "things" data. To evaluate our IoT service model, a weather monitoring system and its associated services are implemented using node.js [31]. The service data is mapped to SSN ontology for generating context-rich RDF data. This way, the proposed IoT service model can expose the device profile to the user and incorporate relevant context information with the things data.

We propose a tool prototype that allows the evolution of goal models in changing business environments. Like jUCMNav, the tool supports annotated goal models where goals, tasks, and resources may be annotated with specific contexts. Softgoal context annotations and their interpretations are quite complex and left out for the time being. The tool performs a qualitative evaluation for identifying conflicts between annotations. It also performs reconciliation of each conflict and presents the user with conflict-free goal model alternatives.

Traditional discretionary access control (DAC) or mandatory access control (MAC) is not quite effective for remote environment. General role-based access control (RBAC) also has its limitations to control access for applications like remote healthcare due to its static nature. Design of effective access control model is indeed a big challenge for such applications. Fine-grained access control logic capable of adapting changes based on run-time information needs to be considered to meet the requirements of remote healthcare scenarios. In this work, an adaptive access control model is proposed keeping in compliance with state–of-the-art scenario towards ensuring quality of context and trust relationship between owners and users. It focuses on inter-component relationship, where phases are executed either in online or in offline mode to avoid performance bottleneck. Adaptive binding is integrated with application specific workflows. Workflow net models for different scenarios of medical kiosk-based rural healthcare are analyzed to validate proposed access control logic at design time that can reduce the possibility of major faults at run time. Our proposed work supports formal analysis and verification using Workflow Petri Net Designer (WoPeD) tool. Comparative analysis shows how proposed access control model advances the state of art.

Goal model like i* are inherently sequence agnostic whereas standard model checkers like SPIN or NuSMV accept extended finite state models which represent an ordering of state transitions that can occur within a system. These two notions are mutually conflicting and, thus, we cannot check temporal properties (like compliance rules), described using temporal languages (like Linear Temporal Logic (LTL), or Computational Tree Logic (CTL)), on goal models by feeding them as input to a standard model checker. The i*ToNuSMV tool aims to bridge this gap such that the compliance of i* models towards temporal constraints can be verified in the early requirements phase of software development itself.

Service oriented computing (SoC) changes the way of conducting business as these services are often available on a network.As traditional access control approach may not work in the changed environment, protecting business resource from misuse is a big challenge.Again, static allocation of access right to users will not be an efficient solution as SoC environment changes with time.This paper focuses on design of dynamic access control approach for business process.Here, we propose a context and trust aware workflow oriented access framework.Proposed approach focuses on inter-component relationship where phases are executed either in online or offline mode to avoid performance bottleneck.The concept of static binding in role based access model is extended to support dynamic access control by including context awareness and trust relationship between owner and user.Trust is either directly or indirectly dependent on service level agreement (SLA) compliance, quality of service, reputation and provenance (historical data).In this paper, the framework is designed by mapping proposed access model to workflow instances at run-time.It is validated by workflow net model, where workflow instance can be successfully executed without any interruption and can satisfy soundness property while incorporating proposed access control approach.

An efficient and flexible business process not only helps an organization to meet the requirements of the evolving surroundings but also may facilitate a competitive advantage over other companies towards delivering the desired services. This is even more critical for an emerging paradigm like cloud based deployment. In this paper, we introduce a novel mechanism to generate the business process suitable for specific organizations. The approach provides an automated way to build the possible business processes for a given set of tasks that fulfills the goal and satisfies the constraints of an organization. In step 1, we show how to generate the finite space of all possible designs for a given set of tasks. Secondly, we accumulate the effect of each step to deduce the final effect of each possible process design and to ensure that the redesigned set of steps still realizes the service goal. The designs not meeting the service goals are eliminated from the space. In step 3, the rest of the designs are checked for the constraint satisfaction subject to some specific cases. The framework provides a comprehensive, both syntactically and semantically correct, consistent business process generation methodology that adheres to the target business goals and constraints.

Software transactional memory (STM) is one of the techniques used towards achieving non-blocking process synchronization in multi-threaded computing environment. In spite of its high potential, one of the major limitations of transactional memory (TM) is that in order to ensure data consistency as well as progress condition, TM often forces transactions to abort. This paper proposes a new concurrency control mechanism. It starts with the existing TM implementations for obstruction freedom and eventually builds a new STM methodology. The primary objective is to reduce aborting of transactions in some typical scenarios. A programming model is described for a chain of update transactions that share the same data object among themselves. Using the proposed approach, any new update transaction appended in this chain need not wait for the earlier transactions to finish. The proposed STM allows wait-free, non-blocking implementation of a mix of read and multiple update transactions on the same shared data object with higher throughput.

Smart Grid is an integrated power grid with a. reliable, communication network running in parallel towards providing two way communications in the grid.It's trivial to mention that a network like this would connect a huge number of IP-enabled devices.IPv6 that offers 18-bit address space becomes an obvious choice in this context.In a smart grid, functionalities like neighborhood discovery, autonomic address configuration of a node or its router identification may often be invoked whenever newer equipments are introduced for capacity enhancement at some level of hierarchy.In IPv6, these basic functionalities like neighborhood discovery, autonomic address configuration of networking require to use Internet Control Message Protocol version 6 (ICMPv6).Such usage may lead to security breaches in the grid as a result of possible abuses of ICMPv6 protocol.In this paper, some potential newer attacks on Smart Grid have been discussed.Subsequently, intrusion prevention mechanisms for these attacks are proposed to plugin the threats.

ABSTRACT Wireless mesh networks (WMNs) are proliferating as one of the key technologies of the next‐generation networks. Security is one of the prime concerns towards actual implementation of any network technology for commercial applications. Network security has intrinsically two approaches—prevention based and detection based. Implementing firewalls or intrusion prevention techniques is often not an attractive solution for energy‐constrained network nodes such as mobile ad hoc network (MANET) nodes or mesh clients in WMNs. However, in the era of pervasive and ubiquitous computing, commercial transactions are performed on the move and over portable devices such as cell phones and laptops. These devices have energy constraints, and hence, one cannot afford to adopt security measures with high computational overhead. This influences a shift in paradigm from active intrusion prevention to passive intrusion detection. In this paper, a new cluster‐oriented reward‐based intrusion detection system (CORIDS) has been proposed for WMNs. The performance of CORIDS has been evaluated using the Qualnet network simulator. Simulation results also establish superiority of CORIDS over Misbehavior Detection Algorithm, another recent trust‐based IDS for WMN, both in terms of higher detection efficiency and lower false positives. Copyright © 2013 John Wiley & Sons, Ltd.

Data warehouse represents multi-dimensional data suitable for analytical processing and logically data are organized in the form of data cube or cuboid. Data warehouse actually represents a business theme which is called fact table. The cuboid that identifies the complete fact table is called base cuboid. The all possible combination of the cuboids that could be generated from base cuboid corresponds to lattice structure. A lattice consists of numbers of cuboids. In real life, all these cuboids may not be important for business analysis. Thus all of them are not always called during business processing. The cuboids that are referred in different applications are fetched from diverse memory hierarchy such as cache memory, primary memory and secondary memory. The different execution speed of the respective memory element is taken into account which forms a memory hierarchy. The focus of this research work is to dynamically identify the most cost effective path within the lattice structure of cuboids to minimize the query access time having the knowledge of existing cuboid location at different memory elements.

Abstract Mobilead hocnetworks (MANET) are highly vulnerable to attacks due to multiple factors including the open medium, dynamically changing network topology, cooperative algorithms, and lack of centralized monitoring. Besides slowing down the network, the traditional way of using firewalls and cryptography often fails to detect different types of attacks. The lack of infrastructures in MANETs makes the detection and control of security hazards all the more difficult. In this paper, we present a new, cluster based Black Hole Intrusion Detection System (BHIDS) for mobile,ad hocnetworks. The features that are considered for BHIDS include mobility of nodes, variation in number of attacking nodes, packet delivery rate, density of the network, etc. The nodes in the network form a two‐layered cluster. This helps splitting the processing and communication overhead between the cluster heads at Layer 1 and 2. The proposed IDS algorithm has been tested on a simulated network using the NS simulator. The performance graphs show marked improvement as far as packet dropping is concerned. Copyright © 2009 John Wiley & Sons, Ltd.

This paper proposes a new token-based mutual exclusion algorithm for directed graph topology, with or without cycles. In one of our earlier works, we have introduced a token based algorithm assuming an inverted tree topology. Such a stable, hierarchical topology is quite unrealistic for mobile networks due to frequent link failures and node mobility. The proposed solution overcomes this. Besides maintaining the correctness in terms of liveness and safety, the proposed algorithm ensures fairness in allocating the token amongst the competing processes. The algorithm offers solution paths even in presence of link failures.

This paper presents a new logical topology SBS-net, a scalable barrel shifter network to be used as a logical topology over an all-optical network using WDM. The major emphasis of the present work is to improve upon the scalability issue. This SBS-net connects any arbitrary numbers of nodes as opposed to the barrel shifter, de Bruijn graph and Shufflenet. The average hopping distance between two nodes using this topology is smaller compared to that in de Bruijn graph, Shufflenet & GEM net.

This paper proposes to structurise the analysis of the performance of Multistage Interconnection Networks (MINs). A new type of High level net, named Modified Petri net (MP-net) which has subsequently been refined to S-net, has been defined in the process. Essentially, a variation of Coloured and Stochastic nets, this S-net has been shown to be a very effective tool for dynamic modelling of MINs. The results reported so far in the context of performance estimation of MINs, are mainly based on direct combinatorial analysis of the concerned networks with very little consideration towards the modelling aspects. The outcome of the present research work may be utilized for modelling of a wide range of MINs consisting of 2/spl times/2 crossbar switches. Multistage redundant path networks like Omega and non-redundant path networks such as Baseline network have been considered and modelled with S-net as a case study. It has also been established that using S-net, a MIN of N/spl times/N size can be modelled with 3N/2 number of places as against O(Nlog/sub 2/N) no. of switching elements for the equivalent MIN. Using the S-net model connectivity status of constituent cross-bar switches of a MIN, has been represented in a matrix, proposed to be termed as Control matrix. An algorithm has been developed to study and modify entries of the control matrix to analyse performance of MIN using S-net model.