{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T08:30:18Z","timestamp":1765269018740,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,6,23]],"date-time":"2024-06-23T00:00:00Z","timestamp":1719100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2139034"],"award-info":[{"award-number":["2139034"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,6,23]]},"DOI":"10.1145\/3649329.3658252","type":"proceedings-article","created":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T19:27:22Z","timestamp":1731007642000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Beyond Conventional Defenses: Proactive and Adversarial-Resilient Hardware Malware Detection using Deep Reinforcement Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5072-2955","authenticated-orcid":false,"given":"Zhangying","family":"He","sequence":"first","affiliation":[{"name":"Department of Computer Engineering and Computer Science, California State University, Long Beach, Long Beach, CA, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8904-4699","authenticated-orcid":false,"given":"Houman","family":"Homayoun","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of California, Davis, Davis, CA, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6423-0145","authenticated-orcid":false,"given":"Hossein","family":"Sayadi","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering and Computer Science, California State University, Long Beach, Long Beach, CA, United States"}]}],"member":"320","published-online":{"date-parts":[[2024,11,7]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"V. Ballet et al. 2019. Imperceptible Adversarial Attacks on Tabular Data. arXiv:1911.03274 [stat.ML]"},{"key":"e_1_3_2_1_2_1","unstructured":"G. Brockman et al. 2016. OpenAI Gym. arXiv:1606.01540"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"N. Carlini and D. Wagner. 2017. Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods. arXiv:1705.07263","DOI":"10.1145\/3128572.3140444"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"J. Demme et al. 2013. On the Feasibility of Online Malware Detection with Performance Counters. In ISCA. ACM 559--570.","DOI":"10.1145\/2485922.2485970"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"A. Dhavlle et al. 2021. HMD-Hardener: Adversarially Robust and Efficient Hardware-Assisted Runtime Malware Detection. In DATE. 1769--1774.","DOI":"10.23919\/DATE51398.2021.9474036"},{"key":"e_1_3_2_1_6_1","first-page":"1","article-title":"Adversarial Attack on Microarchitectural Events Based Malware Detectors. In DAC. ACM","volume":"164","author":"Dinakarrao S. M. P.","year":"2019","unstructured":"S. M. P. Dinakarrao et al. 2019. Adversarial Attack on Microarchitectural Events Based Malware Detectors. In DAC. ACM, Article 164, 1--6 pages.","journal-title":"Article"},{"key":"e_1_3_2_1_7_1","volume-title":"Adversarial Examples for Malware Detection. In ESORICS","author":"Grosse K.","year":"2017","unstructured":"K. Grosse et al. 2017. Adversarial Examples for Malware Detection. In ESORICS 2017. Springer, Cham, 62--79."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123939.3123972"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"A. P. Kuruvila et al. 2021. Defending Hardware-Based Malware Detectors Against Adversarial Attacks. IEEE TCAD 40 9 (2021).","DOI":"10.1109\/TCAD.2020.3026960"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.02.075"},{"key":"e_1_3_2_1_11_1","unstructured":"V. Mnih et al. 2016. Asynchronous Methods for Deep Reinforcement Learning. In ICML. 1928--1937."},{"key":"e_1_3_2_1_12_1","unstructured":"M. Nicolae et al. 2019. Adversarial Robustness Toolbox v1.0.0. arXiv:1807.01069"},{"key":"e_1_3_2_1_13_1","unstructured":"N. Papernot et al. 2016. Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples. arXiv:1605.07277"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"I. Rosenberg et al. 2018. Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers. In RAID. Springer Cham 490--510.","DOI":"10.1007\/978-3-030-00470-5_23"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"I. Rosenberg et al. 2020. Query-Efficient Black-Box Attack Against Sequence-Based Malware Classifiers. arXiv:1804.08778","DOI":"10.1145\/3427228.3427230"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"I. Rosenberg et al. 2021. Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain. arXiv:2007.02407","DOI":"10.1145\/3453158"},{"key":"e_1_3_2_1_17_1","volume-title":"Mutual Information between Discrete and Continuous Data Sets. PLoS ONE 9","author":"Ross B. C.","year":"2014","unstructured":"B. C. Ross. 2014. Mutual Information between Discrete and Continuous Data Sets. PLoS ONE 9 (2014)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"H. Sayadi et al. 2018. Ensemble Learning for Effective Run-time Hardware-based Malware Detection: A Comprehensive Analysis and Classification. In DAC. 1--6.","DOI":"10.1145\/3195970.3196047"},{"key":"e_1_3_2_1_19_1","volume-title":"Tabular Data: Deep Learning is Not All You Need. arXiv:2106.03253","author":"Shwartz-Ziv R.","year":"2021","unstructured":"R. Shwartz-Ziv and A. Armon. 2021. Tabular Data: Deep Learning is Not All You Need. arXiv:2106.03253"},{"key":"e_1_3_2_1_20_1","unstructured":"O. Suciu et al. 2018. When Does Machine Learning FAIL? Generalized Transfer-ability for Evasion and Poisoning Attacks. In USENIX Security. 1299--1316."},{"key":"e_1_3_2_1_21_1","unstructured":"C. Szegedy et al. 2014. Intriguing Properties of Neural Networks. arXiv:1312.6199"},{"key":"e_1_3_2_1_22_1","volume-title":"MANIS: Evading Malware Detection System on Graph Structure. In SAC. ACM, 1688--1695.","author":"Xu P.","year":"2020","unstructured":"P. Xu et al. 2020. MANIS: Evading Malware Detection System on Graph Structure. In SAC. ACM, 1688--1695."}],"event":{"name":"DAC '24: 61st ACM\/IEEE Design Automation Conference","sponsor":["SIGDA ACM Special Interest Group on Design Automation","IEEE-CEDA","SIGBED ACM Special Interest Group on Embedded Systems"],"location":"San Francisco CA USA","acronym":"DAC '24"},"container-title":["Proceedings of the 61st ACM\/IEEE Design Automation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3649329.3658252","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3649329.3658252","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3649329.3658252","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:01Z","timestamp":1750295881000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3649329.3658252"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,23]]},"references-count":22,"alternative-id":["10.1145\/3649329.3658252","10.1145\/3649329"],"URL":"https:\/\/doi.org\/10.1145\/3649329.3658252","relation":{},"subject":[],"published":{"date-parts":[[2024,6,23]]},"assertion":[{"value":"2024-11-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}