{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T14:34:05Z","timestamp":1780756445896,"version":"3.54.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>Attacks in cyber-physical systems (CPS) which manipulate sensor\n\nreadings can cause enormous physical damage if undetected.\n\nDetection of attacks on sensors \n\nis crucial to mitigate this issue.\n\nWe study supervised regression as a means to detect anomalous sensor\n\nreadings, where each sensor's measurement is predicted as a function\n\nof other sensors.\n\nWe show that several common learning approaches in this context\n\nare still vulnerable to stealthy attacks, which carefully\n\nmodify readings of compromised sensors to cause desired damage while\n\nremaining undetected.\n\nNext, we model the interaction between the CPS defender and attacker\n\nas a Stackelberg game in which the defender chooses detection\n\nthresholds, while the attacker deploys a stealthy attack in response.\n\nWe present a heuristic algorithm for finding an approximately optimal threshold for\n\nthe defender in this game, and show that it increases system\n\nresilience to attacks without significantly increasing the false alarm rate.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/524","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"3769-3775","source":"Crossref","is-referenced-by-count":32,"title":["Adversarial Regression for Detecting Attacks in Cyber-Physical Systems"],"prefix":"10.24963","author":[{"given":"Amin","family":"Ghafouri","sequence":"first","affiliation":[{"name":"Cruise Automation, San Francisco, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yevgeniy","family":"Vorobeychik","sequence":"additional","affiliation":[{"name":"Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xenofon","family":"Koutsoukos","sequence":"additional","affiliation":[{"name":"Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","theme":"Artificial Intelligence","location":"Stockholm, Sweden","acronym":"IJCAI-2018","number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2018,7,13]]},"end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:53:39Z","timestamp":1530755619000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/524"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/524","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}