9,191 research outputs found

    A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

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    In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks

    A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

    Get PDF
    In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks

    Information Warfare-Worthy Jamming Attack Detection Mechanism for Wireless Sensor Networks Using a Fuzzy Inference System

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    The proposed mechanism for jamming attack detection for wireless sensor networks is novel in three respects: firstly, it upgrades the jammer to include versatile military jammers; secondly, it graduates from the existing node-centric detection system to the network-centric system making it robust and economical at the nodes, and thirdly, it tackles the problem through fuzzy inference system, as the decision regarding intensity of jamming is seldom crisp. The system with its high robustness, ability to grade nodes with jamming indices, and its true-detection rate as high as 99.8%, is worthy of consideration for information warfare defense purposes

    Adversarial jamming attacks and defense strategies via adaptive deep reinforcement learning

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    As the applications of deep reinforcement learning (DRL) in wireless communications grow, sensitivity of DRL based wireless communication strategies against adversarial attacks has started to draw increasing attention. In order to address such sensitivity and alleviate the resulting security concerns, we in this paper consider a victim user that performs DRL-based dynamic channel access, and an attacker that executes DRLbased jamming attacks to disrupt the victim. Hence, both the victim and attacker are DRL agents and can interact with each other, retrain their models, and adapt to opponents' policies. In this setting, we initially develop an adversarial jamming attack policy that aims at minimizing the accuracy of victim's decision making on dynamic channel access. Subsequently, we devise defense strategies against such an attacker, and propose three defense strategies, namely diversified defense with proportional-integral-derivative (PID) control, diversified defense with an imitation attacker, and defense via orthogonal policies. We design these strategies to maximize the attacked victim's accuracy and evaluate their performances.Comment: 13 pages, 24 figure
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