28,690 research outputs found

    A Candour-based Trust and Reputation Management System for Mobile Ad Hoc Networks

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    The decentralized administrative controlled-nature of mobile ad hoc networks (MANETs) presents security vulnerabilities which can lead to attacks such as malicious modification of packets. To enhance security in MANETs, Trust and Reputation Management systems (TRM) have been developed to serve as measures in mitigating threats arising from unusual behaviours of nodes. In this paper we propose a candour-based trust and reputation system which measures and models reputation and trust propagation in MANETs. In the proposed model Dirichlet Probability Distribution is employed in modelling the individual reputation of nodes and the trust of each node is computed based on the node’s actual network performance and the quality of the recommendations it gives about other nodes. Cooperative nodes in our model will be rewarded for expanding their energy in forwarding packets for other nodes or for disseminating genuine recommenda-tions. Uncooperative nodes are isolated and denied the available network resources. We employed the Ruffle algorithm which will ensure that cooperative nodes are allowed to activate sleep mode when their service is not required in forwarding packets for its neighbouring trustworthy nodes. The proposed TRM system enshrines fairness in its mode of operation as well as creating an enabling environment free from bias. It will also ensure a connected and capacity preserving network of trustworthy node

    TRUST BASED SECURE AODV IN MANET

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    Abstract- The nature of self-organization and the limitation of individual resources, MANET always confront security and selfishness issues. In this thesis, we design trusted routing protocols using trusted frame works and intrusion detection system (secure protocol) f or MANET. Trust combination algorithms and trust mapping functions are provided in this model, where the former can aggregate different opinions together to get a new recommendation opinion. Based on this trust model, we design our trusted routing protocols for MANET called TAODV on top of Ad Hoc On-demand Distance Vector (AODV) routing protocol. We extend the routing table and the routing messages of ADOV with trust information which can be updated directly through monitoring in the neighborhood. When performing trusted routing discovery, unlike those cryptographic schemes that perform signature generation or verification at every routing packet, we just combine the recommen ded opinions together and make a routing judgment based on each element of the new opinion. In this way the computation overhead can be largely reduced, and the trustworthiness of the routing procedure can be guaranteed as well. In this thesis, we implement the security and sel fishness issues of wireless networks, either in non-cooperative form or in cooperative form. Our results show that the cumulative utilities of cooperative nodes are increased steadily and the selfish nodes cannot get more utilities by behaving selfishly than cooperatively

    MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

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    Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A

    PROTECT: Proximity-based Trust-advisor using Encounters for Mobile Societies

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    Many interactions between network users rely on trust, which is becoming particularly important given the security breaches in the Internet today. These problems are further exacerbated by the dynamics in wireless mobile networks. In this paper we address the issue of trust advisory and establishment in mobile networks, with application to ad hoc networks, including DTNs. We utilize encounters in mobile societies in novel ways, noticing that mobility provides opportunities to build proximity, location and similarity based trust. Four new trust advisor filters are introduced - including encounter frequency, duration, behavior vectors and behavior matrices - and evaluated over an extensive set of real-world traces collected from a major university. Two sets of statistical analyses are performed; the first examines the underlying encounter relationships in mobile societies, and the second evaluates DTN routing in mobile peer-to-peer networks using trust and selfishness models. We find that for the analyzed trace, trust filters are stable in terms of growth with time (3 filters have close to 90% overlap of users over a period of 9 weeks) and the results produced by different filters are noticeably different. In our analysis for trust and selfishness model, our trust filters largely undo the effect of selfishness on the unreachability in a network. Thus improving the connectivity in a network with selfish nodes. We hope that our initial promising results open the door for further research on proximity-based trust
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