秘密攻击信息素群

Janiece Kelly, Seth Richter, Mina Guirguis
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引用次数: 2

摘要

在多智能体系统中,采用数字信息素群算法协调智能体实现复杂智能行为。研究表明,信息素群系统具有通用性强、效率高、抗故障能力强等特点,适用于边境管制、区域覆盖、目标跟踪、搜索救援等多种场景。由于它们依赖于无线通信信道,容易受到干扰和干扰攻击,因此研究这些系统在恶意条件下的安全性变得非常重要。本文研究了信息素群在不同干扰攻击下的安全性。特别是,我们暴露了新型的隐形攻击,旨在最大限度地对蜂群造成伤害,同时降低暴露的风险。与完全拒绝服务(DoS)攻击不同,这种攻击会根据蜂群的当前状态选择要干扰的信号。我们通过新的指标评估了攻击的影响,这些指标揭示了损害和成本之间的权衡。我们的研究结果表明,暴露的攻击比传统的dos类攻击更有效。我们的结果是通过在我们的移动网络物理系统实验室中使用许多iRobot Create机器人的模拟实验和实际物理实现获得的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stealthy attacks on pheromone swarming
In multi-agent systems, digital pheromone swarming algorithms are used to coordinate agents to achieve complex and intelligent behaviors. Studies have shown that pheromone swarming systems are versatile, efficient and resilient to failures, and thus are applicable in various scenarios such as border control, area coverage, target tracking, search and rescue, etc. Due to their reliance on wireless communication channels - which are vulnerable to interference and jamming attacks - it becomes important to study the security of these systems under malicious conditions. In this paper, we investigate the security of pheromone swarming under different types of jamming attacks. In particular, we expose new types of stealthy attacks that aim to maximize the damage inflicted on the swarm while reducing the risk of exposure. Unlike complete Denial of Service (DoS) attacks, the attacks exposed select which signal to interfere with based on the current state of the swarm. We have assessed the impact of the attacks through new metrics that expose the tradeoff between damage and cost. Our results show that the exposed attacks are more potent than traditional DoS-like attacks. Our results are obtained from simulation experiments and real physical implementation using a number of iRobot Create robots in our Mobile Cyber-Physical Systems lab.
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