998 research outputs found

    Countering Node Misbehavior Attacks using Trust Based Secure Routing Protocol

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    Wireless sensor networks have gained remarkable appreciation over the last few years. Despite significant advantages and tremendous applications, WSN is vulnerable to variety of attacks. Due to resource constraint nature of WSN, applicability of traditional security solutions is debatable. Although cryptography, authentication and confidentiality measures help in preventing specific types of attacks but they cannot safeguard against node misbehavior attacks and come at significant cost. To address this problem, we propose a Trust Based Secure Routing Protocol (TBSRP) which adopts on-demand routing principle and relies on distributed trust model for the detection and isolation of misbehaving nodes. The TBSRP aims to establish shortest path that contain all trusted nodes, identify packet forwarding misbehavior caused by malicious and faulty nodes and reroute the traffic to other reliable paths. The performance of TBSRP is evaluated in terms of packet delivery ratio, average end-to-end delay, normalized routing load and average throughput. Simulations results show that TBSRP can achieve both high delivery ratio and throughput in presence of various numbers of misbehaving and faulty nodes

    Algebraic Watchdog: Mitigating Misbehavior in Wireless Network Coding

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    We propose a secure scheme for wireless network coding, called the algebraic watchdog. By enabling nodes to detect malicious behaviors probabilistically and use overheard messages to police their downstream neighbors locally, the algebraic watchdog delivers a secure global self-checking network. Unlike traditional Byzantine detection protocols which are receiver-based, this protocol gives the senders an active role in checking the node downstream. The key idea is inspired by Marti et al.'s watchdog-pathrater, which attempts to detect and mitigate the effects of routing misbehavior. As an initial building block of a such system, we first focus on a two-hop network. We present a graphical model to understand the inference process nodes execute to police their downstream neighbors; as well as to compute, analyze, and approximate the probabilities of misdetection and false detection. In addition, we present an algebraic analysis of the performance using an hypothesis testing framework that provides exact formulae for probabilities of false detection and misdetection. We then extend the algebraic watchdog to a more general network setting, and propose a protocol in which we can establish trust in coded systems in a distributed manner. We develop a graphical model to detect the presence of an adversarial node downstream within a general multi-hop network. The structure of the graphical model (a trellis) lends itself to well-known algorithms, such as the Viterbi algorithm, which can compute the probabilities of misdetection and false detection. We show analytically that as long as the min-cut is not dominated by the Byzantine adversaries, upstream nodes can monitor downstream neighbors and allow reliable communication with certain probability. Finally, we present simulation results that support our analysis.Comment: 10 pages, 10 figures, Submitted to IEEE Journal on Selected Areas in Communications (JSAC) "Advances in Military Networking and Communications

    A Multi-hop Multi-source Algebraic Watchdog

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    In our previous work "An Algebraic Watchdog for Wireless Network Coding", we proposed a new scheme in which nodes can detect malicious behaviors probabilistically, police their downstream neighbors locally using overheard messages; thus, provide a secure global "self-checking network". As the first building block of such a system, we focused on a two-hop network, and presented a graphical model to understand the inference process by which nodes police their downstream neighbors and to compute the probabilities of misdetection and false detection. In this paper, we extend the Algebraic Watchdog to a more general network setting, and propose a protocol in which we can establish "trust" in coded systems in a distributed manner. We develop a graphical model to detect the presence of an adversarial node downstream within a general two-hop network. The structure of the graphical model (a trellis) lends itself to well-known algorithms, such as Viterbi algorithm, that can compute the probabilities of misdetection and false detection. Using this as a building block, we generalize our scheme to multi-hop networks. We show analytically that as long as the min-cut is not dominated by the Byzantine adversaries, upstream nodes can monitor downstream neighbors and allow reliable communication with certain probability. Finally, we present preliminary simulation results that support our analysis.Comment: 5 pages, 2 figures, to appear in IEEE ITW Dublin 201

    A Taxonomy on Misbehaving Nodes in Delay Tolerant Networks

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    Delay Tolerant Networks (DTNs) are type of Intermittently Connected Networks (ICNs) featured by long delay, intermittent connectivity, asymmetric data rates and high error rates. DTNs have been primarily developed for InterPlanetary Networks (IPNs), however, have shown promising potential in challenged networks i.e. DakNet, ZebraNet, KioskNet and WiderNet. Due to unique nature of intermittent connectivity and long delay, DTNs face challenges in routing, key management, privacy, fragmentation and misbehaving nodes. Here, misbehaving nodes i.e. malicious and selfish nodes launch various attacks including flood, packet drop and fake packets attack, inevitably overuse scarce resources (e.g., buffer and bandwidth) in DTNs. The focus of this survey is on a review of misbehaving node attacks, and detection algorithms. We firstly classify various of attacks depending on the type of misbehaving nodes. Then, detection algorithms for these misbehaving nodes are categorized depending on preventive and detective based features. The panoramic view on misbehaving nodes and detection algorithms are further analyzed, evaluated mathematically through a number of performance metrics. Future directions guiding this topic are also presented
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