Optimal denial‐of‐service attack scheduling for remote state estimation with time‐varying interference power

Author:

Yang Xinxin1ORCID,Ni Yuqing1ORCID,Wu Zhe2,Yang Wen3,Liu Fei1ORCID

Affiliation:

1. The Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things Engineering, Jiangnan University Wuxi China

2. Department of Chemical and Biomolecular Engineering National University of Singapore Singapore

3. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education East China University of Science and Technology Shanghai China

Abstract

AbstractThis article examines resource scheduling optimization for cyber‐physical systems that include a smart sensor, a remote estimator, and an attacker. The attacker's objective is to use denial‐of‐service (DoS) attack to jam the wireless channel, causing packet loss and reducing system performance. We consider a more realistic scenario where other interfering sources exist and conduct research based on the signal‐to‐interference‐plus‐noise ratio (SINR) model. Through this model, we investigate two cases: constant high or low interference power and time‐varying interference power. Different levels of attack power lead to varying packet loss rates, and the same attack power may result in different packet loss rates in different interference environments. Therefore, the attacker needs to consider the impact of other interferences to find the optimal attack strategy that increases the estimation error of the information‐physical system while reducing energy consumption. We describe this optimization problem in a Markov decision process (MDP) framework and demonstrate the existence of an optimal deterministic Markovian strategy. We also establish the monotonicity of the optimal strategy in two different cases and investigate the extreme case. Simulation results support our theoretical results.

Funder

Higher Education Discipline Innovation Project

National Natural Science Foundation of China

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3