Craig Bakker, Arnab Bhattacharya, S. Chatterjee, D. Vrabie
{"title":"Metagames and Hypergames for Deception-Robust Control","authors":"Craig Bakker, Arnab Bhattacharya, S. Chatterjee, D. Vrabie","doi":"10.1145/3439430","DOIUrl":null,"url":null,"abstract":"Increasing connectivity to the Internet for remote monitoring and control has made cyber-physical systems more vulnerable to deliberate attacks; purely cyber attacks can thereby have physical consequences. Long-term, stealthy attacks such as Stuxnet can be described as Advanced Persistent Threats (APTs). Here, we extend our previous work on hypergames and APTs to develop hypergame-based defender strategies that are robust to deception and do not rely on attack detection. These strategies provide provable bounds—and provably optimal bounds—on the attacker payoff. Strategies based on Bayesian priors do not provide such bounds. We then numerically demonstrate our approach on a building control subsystem and discuss next steps in extending this approach toward an operational capability.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":"5 1","pages":"1 - 25"},"PeriodicalIF":2.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3439430","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Cyber-Physical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3439430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 11
Abstract
Increasing connectivity to the Internet for remote monitoring and control has made cyber-physical systems more vulnerable to deliberate attacks; purely cyber attacks can thereby have physical consequences. Long-term, stealthy attacks such as Stuxnet can be described as Advanced Persistent Threats (APTs). Here, we extend our previous work on hypergames and APTs to develop hypergame-based defender strategies that are robust to deception and do not rely on attack detection. These strategies provide provable bounds—and provably optimal bounds—on the attacker payoff. Strategies based on Bayesian priors do not provide such bounds. We then numerically demonstrate our approach on a building control subsystem and discuss next steps in extending this approach toward an operational capability.