2,020 research outputs found

    Adaptive trust and reputation system as a security service in group communications

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    Group communications has been facilitating many emerging applications which require packet delivery from one or more sender(s) to multiple receivers. Owing to the multicasting and broadcasting nature, group communications are susceptible to various kinds of attacks. Though a number of proposals have been reported to secure group communications, provisioning security in group communications remains a critical and challenging issue. This work first presents a survey on recent advances in security requirements and services in group communications in wireless and wired networks, and discusses challenges in designing secure group communications in these networks. Effective security services to secure group communications are then proposed. This dissertation also introduces the taxonomy of security services, which can be applied to secure group communications, and evaluates existing secure group communications schemes. This dissertation work analyzes a number of vulnerabilities against trust and reputation systems, and proposes a threat model to predict attack behaviors. This work also considers scenarios in which multiple attacking agents actively and collaboratively attack the whole network as well as a specific individual node. The behaviors may be related to both performance issues and security issues. Finally, this work extensively examines and substantiates the security of the proposed trust and reputation system. This work next discusses the proposed trust and reputation system for an anonymous network, referred to as the Adaptive Trust-based Anonymous Network (ATAN). The distributed and decentralized network management in ATAN does not require a central authority so that ATAN alleviates the problem of a single point of failure. In ATAN, the trust and reputation system aims to enhance anonymity by establishing a trust and reputation relationship between the source and the forwarding members. The trust and reputation relationship of any two nodes is adaptive to new information learned by these two nodes or recommended from other trust nodes. Therefore, packets are anonymously routed from the \u27trusted\u27 source to the destination through \u27trusted\u27 intermediate nodes, thereby improving anonymity of communications. In the performance analysis, the ratio of the ATAN header and data payload is around 0.1, which is relatively small. This dissertation offers analysis on security services on group communications. It illustrates that these security services are needed to incorporate with each other such that group communications can be secure. Furthermore, the adaptive trust and reputation system is proposed to integrate the concept of trust and reputation into communications. Although deploying the trust and reputation system incurs some overheads in terms of storage spaces, bandwidth and computation cycles, it shows a very promising performance that enhance users\u27 confidence in using group communications, and concludes that the trust and reputation system should be deployed as another layer of security services to protect group communications against malicious adversaries and attacks

    IoT trust and reputation: a survey and taxonomy

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    IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilized across the globe by the end of 2030. To maximize the capability of these connected entities, trust and reputation among IoT entities is essential. Several trust management models have been proposed in the IoT environment; however, these schemes have not fully addressed the IoT devices features, such as devices role, device type and its dynamic behavior in a smart environment. As a result, traditional trust and reputation models are insufficient to tackle these characteristics and uncertainty risks while connecting nodes to the network. Whilst continuous study has been carried out and various articles suggest promising solutions in constrained environments, research on trust and reputation is still at its infancy. In this paper, we carry out a comprehensive literature review on state-of-the-art research on the trust and reputation of IoT devices and systems. Specifically, we first propose a new structure, namely a new taxonomy, to organize the trust and reputation models based on the ways trust is managed. The proposed taxonomy comprises of traditional trust management-based systems and artificial intelligence-based systems, and combine both the classes which encourage the existing schemes to adapt these emerging concepts. This collaboration between the conventional mathematical and the advanced ML models result in design schemes that are more robust and efficient. Then we drill down to compare and analyse the methods and applications of these systems based on community-accepted performance metrics, e.g. scalability, delay, cooperativeness and efficiency. Finally, built upon the findings of the analysis, we identify and discuss open research issues and challenges, and further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin

    A Survey on Trust Computation in the Internet of Things

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    Internet of Things defines a large number of diverse entities and services which interconnect with each other and individually or cooperatively operate depending on context, conditions and environments, produce a huge personal and sensitive data. In this scenario, the satisfaction of privacy, security and trust plays a critical role in the success of the Internet of Things. Trust here can be considered as a key property to establish trustworthy and seamless connectivity among entities and to guarantee secure services and applications. The aim of this study is to provide a survey on various trust computation strategies and identify future trends in the field. We discuss trust computation methods under several aspects and provide comparison of the approaches based on trust features, performance, advantages, weaknesses and limitations of each strategy. Finally the research discuss on the gap of the trust literature and raise some research directions in trust computation in the Internet of Things
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