A Trust Management Framework for Decision Support Systems

In the era of information explosion, it is critical to develop a framework which can extract useful information and help people to make “educated” decisions. In our lives, whether we are aware of it, trust has turned out to be very helpful for us to make decisions. At the same time, cognitive trust, especially in large systems, such as Facebook, Twitter, and so on, needs support from computer systems. Therefore, we need a framework that can effectively, but also intuitively, let people express their trust, and enable the system to automatically and securely summarize the massive amounts of trust information, so that a user of the system can make “educated” decisions, or at least not blind decisions. Inspired by the similarities between human trust and physical measurements, this dissertation proposes a measurement theory based trust management framework. It consists of three phases: trust modeling, trust inference, and decision making. Instead of proposing specific trust inference formulas, this dissertation proposes a fundamental framework which is flexible and can be adapted by many different inference formulas. Validation experiments are done on two data sets: the Epinions.com data set and the Twitter data set. This dissertation also adapts the measurement theory based trust management framework for two decision support applications. In the first application, the real stock market data is used as ground truth for the measurement theory based trust management framework. Basically, the correlation between the sentiment expressed on Twitter and stock market data is measured. Compared with existing works which do not differentiate tweets’ authors, this dissertation analyzes trust among stock investors on Twitter and uses the trust network to differentiate tweets’ authors. The results show that by using the measurement theory based trust framework, Twitter sentiment valence is able to reflect abnormal stock returns better than treating all the authors as equally important or weighting them by their number of followers. In the second application, the measurement theory based trust management framework is used to help to detect and prevent from being attacked in cloud computing scenarios. In this application, each single flow is treated as a measurement. The simulation results show that the measurement theory based trust management framework is able to provide guidance for cloud administrators and customers to make decisions, e.g. migrating tasks from suspect nodes to trustworthy nodes, dynamically allocating resources according to trust information, and managing the trade-off between the degree of redundancy and the cost of resources

A Survey on Trust Computation in the Internet of Things

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

Evaluated reputation-based trust for WSN security

During the last years, Wireless Sensor Networks (WSNs) and its applications have obtained considerable momentum. However, security and power limits of WSNs are still important matters. Many existing approaches at most concentrate on cryptography to improve data authentication and integrity but this addresses only a part of the security problem without consideration for high energy consumption. Monitoring behavior of node neighbors using reputation and trust models improves the security of WSNs and maximizes the lifetime for it. However, a few of previous studies take into consideration security threats and energy consumption at the same time. Under these issues Modified Reputation-Based Trust model proposed and optimized for security strength. During evaluation of the model with well-known models two security threats (oscillating and collusion) were applied in order to measure the accuracy, scalability, trustworthiness and energy consumption. As a result, the effects of collusion and oscillating on proposed model are minimized and energy consumption for dynamic networks reduced. Also, simulation results show that MRT has better average accuracy and less average path length than other mechanisms, due to the security and energy aware. Keywords: Wireless Sensor Networks (WSNs), Collusion, Oscillating, Power Consumption, Trust and Reputation Model

Trust management schemes for peer-to-peer networks

Peer-to-peer (P2P) networking enables users with similar interests to exchange, or obtain files. This network model has been proven popular to exchange music, pictures, or software applications. These files are saved, and most likely executed, at the downloading host. At the expense of this mechanism, worms, viruses, and malware find an open front door to the downloading host and gives them a convenient environment for successful proliferation throughout the network. Although virus detection software is currently available, this countermeasure works in a reactive fashion, and in most times, in an isolated manner. A trust management scheme is considered to contain the proliferation of viruses in P2P networks. Specifically, a cooperative and distributed trust management scheme based on a two-layer approach to bound the proliferation of viruses is proposed. The new scheme is called double-layer dynamic trust (DDT) management scheme. The results show that the proposed scheme bounds the proliferation of malware. With the proposed scheme, the number of infected hosts and the proliferation rate are limited to small values. In addition, it is shown that network activity is not discouraged by using the proposed scheme. Moreover, to improve the efficiency on the calculation of trust values of ratio based normalization models, a model is proposed for trust value calculation using a three-dimensional normalization to represent peer activity with more accuracy than that of a conventional ratio based normalization. Distributed network security is also considered, especially in P2P network security. For many P2P systems, including ad hoc networks and online markets, reputation systems have been considered as a solution for mitigating the affects of malicious peers. However, a sybil attack, wherein forging identities is performed to unfairly and arbitrarily influence the reputation of peers in a network or community. To defend against sybil attack, each reported transaction, which is used to calculate trust values, is verified. In this thesis, it is shown that peer reputation alone cannot bound network subversion of a sybil attack. Therefore, a new trust management framework, called Sybildefense, is introduced. This framework combines a trust management scheme with a cryptography mechanism to verify different transaction claims issue by peers, including those bogus claims of sybil peers. To improve the efficiency on the identification of honest peers from sybil peers, a k-means clustering mechanism is adopted. Moreover, to include a list of peer’s trustees in a warning messages is proposed to generate a local table for a peer that it is used to identify possible clusters of sybil peers. The defensive performance of these algorithms are compared under sybil attacks. The performance results show that the proposed framework (Sybildefense) can thwart sybil attacks efficiently

Determining service trustworthiness in inter loud computing environments

Deployment of applications and scientific workflows that require resources from multiple distributed platforms are fuelling the federation of autonomous clouds to create cyber infrastructure environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. In this paper, we present a fully distributed framework that enable interested parties determine the trustworthiness of federated cloud computing entities.<br /

A survey of security issue in multi-agent systems

Multi-agent systems have attracted the attention of researchers because of agents' automatic, pro-active, and dynamic problem solving behaviors. Consequently, there has been a rapid development in agent technology which has enabled us to provide or receive useful and convenient services in a variety of areas such as banking, transportation, e-business, and healthcare. In many of these services, it is, however, necessary that security is guaranteed. Unless we guarantee the security services based on agent-based systems, these services will face significant deployment problems. In this paper, we survey existing work related to security in multi-agent systems, especially focused on access control and trust/reputation, and then present our analyses. We also present existing problems and discuss future research challenges. © Springer Science+Business Media B.V 2011

Report on a Working Session on Security in Wireless Ad Hoc Networks

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