防御协调行为策略攻击的蜂群机器人系统算法

I. Zikratov, T. Zikratova, E. A. Novikov
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引用次数: 0

摘要

问题陈述:设计针对移动多代理机器人系统协调行为策略攻击的防御机制。这类攻击可能通过使用信息拦截、制造和传输虚假信息以及其他不具有可识别的破坏者入侵特征的行为来实施,并导致机器人群做出错误或非最佳决策。工作目的:提高移动多代理机器人系统协调行为策略攻击的检测概率。采用的方法:提出的算法是对自组织机制的进一步发展,使用信任和声誉指标来检测和反击恶意机器人。使用集体探索任务的模仿模型证实了所提方法的准确性。新颖性:该算法基于将达成共识的过程量化为连续的时间段,然后在时间段间和时间段内处理蜂群机器人和恶意机器人在通信过程中产生的信息。结果:实验表明,当恶意机器人的集中度超过 51%时,蜂群能够抵御恶意机器人的协同攻击。这种反击的概率接近 1。已知的同质机器人群破坏性信息影响的检测和反制方法证明,在恶意单元浓度低于 45% 的情况下是有效的。实用意义:所开发的算法可用于多代理机器人系统的安全系统设计,以防止在机器人群之间的互动过程中受到攻击。该算法可成功抵御类似 "51% 攻击 "的协同攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Swarm Robotics System Algorithm for Defense against Coordinated Behavior Strategy Attacks
Problem statement: designing the defense mechanism against coordinated behavior strategy attacks for mobile multiagent robotic systems. Possible attacks of that kind may be carried out by use message interception, creating and transmitting disinformation, and other actions, that does not have identifiable characteristics of saboteur intrusion, and lead to making incorrect or non-optimal decision by group of robots. The purpose of the work: the increase of probability of detection coordinated behavior strategy attacks on mobile multiagent robotic systems. Methods used: proposed algorithm is further development of self organization mechanism, using trust and reputation metrics for detection and counteraction against malicious robots. Accuracy of proposed method is confirmed using imitation model of collective exploration task. The novelty: algorithm is based on quantification of consensus achievement process into consecutive time periods, which is followed by inter- and intraperiod processing of information, produces by robots of the swarm and by malicious robots during communication. The result: experiment shows that the swarm is capable to counteract against coordinated attack of malicious robots, when concentration of malicious units is more than 51 %. The probability of such counteraction is close to 1. Known detection and counteraction methods for destructive informational influence in homogeneous swarms of robots prove to be effective in cases, when concentration of malicious units is less than 45 %. Practical significance: developed algorithm may be used for multiagent robotic systems security system design to protect against attack, executed during interactions between agents of the swarm. Algorithm allows to successfully counteract coordinated attacks similar to «51 percent attack».
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