{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:24:42Z","timestamp":1750220682097,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T00:00:00Z","timestamp":1600646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Institute of Standards and Technology","award":["70NANB18H198"],"award-info":[{"award-number":["70NANB18H198"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,9,21]]},"DOI":"10.1145\/3384217.3385616","type":"proceedings-article","created":{"date-parts":[[2020,8,26]],"date-time":"2020-08-26T04:14:50Z","timestamp":1598415290000},"page":"1-9","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["@PAD"],"prefix":"10.1145","author":[{"given":"Ali I","family":"Ozdagli","sequence":"first","affiliation":[{"name":"Vanderbilt University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlos","family":"Barreto","sequence":"additional","affiliation":[{"name":"Vanderbilt University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xenofon","family":"Koutsoukos","sequence":"additional","affiliation":[{"name":"Vanderbilt University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,9,21]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/IEEESTD.2009.5154067"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/23307706.2017.1397554"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/AINS.2017.8270432"},{"volume-title":"Nonlinear programming: analysis and methods","author":"Avriel Mordecai","key":"e_1_3_2_1_4_1","unstructured":"Mordecai Avriel . 2003. Nonlinear programming: analysis and methods . Courier Corporation . Mordecai Avriel. 2003. Nonlinear programming: analysis and methods. Courier Corporation."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISGT.2018.8403355"},{"volume-title":"Decision and Game Theory for Security, Tansu Alpcan, Yevgeniy Vorobeychik, John S","author":"Barreto Carlos","key":"e_1_3_2_1_6_1","unstructured":"Carlos Barreto and Xenofon Koutsoukos . 2019. Design of Load Forecast Systems Resilient Against Cyber-Attacks . In Decision and Game Theory for Security, Tansu Alpcan, Yevgeniy Vorobeychik, John S . Baras, and Gy\u00f6rgy D\u00e1n (Eds.). Springer International Publishing , Cham , 1--20. Carlos Barreto and Xenofon Koutsoukos. 2019. Design of Load Forecast Systems Resilient Against Cyber-Attacks. In Decision and Game Theory for Security, Tansu Alpcan, Yevgeniy Vorobeychik, John S. Baras, and Gy\u00f6rgy D\u00e1n (Eds.). Springer International Publishing, Cham, 1--20."},{"volume-title":"25th {USENIX} Security Symposium ({USENIX} Security 16). 513--530.","author":"Carlini Nicholas","key":"e_1_3_2_1_7_1","unstructured":"Nicholas Carlini , Pratyush Mishra , Tavish Vaidya , Yuankai Zhang , Micah Sherr , Clay Shields , David Wagner , and Wenchao Zhou . 2016. Hidden voice commands . In 25th {USENIX} Security Symposium ({USENIX} Security 16). 513--530. Nicholas Carlini, Pratyush Mishra, Tavish Vaidya, Yuankai Zhang, Micah Sherr, Clay Shields, David Wagner, and Wenchao Zhou. 2016. Hidden voice commands. In 25th {USENIX} Security Symposium ({USENIX} Security 16). 513--530."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3307772.3328314"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/11856214_4"},{"key":"e_1_3_2_1_10_1","first-page":"1","article-title":"CVXPY: A Python-Embedded Modeling Language for Convex Optimization","volume":"17","author":"Diamond Steven","year":"2016","unstructured":"Steven Diamond and Stephen Boyd . 2016 . CVXPY: A Python-Embedded Modeling Language for Convex Optimization . Journal of Machine Learning Research 17 , 83 (2016), 1 -- 5 . Steven Diamond and Stephen Boyd. 2016. CVXPY: A Python-Embedded Modeling Language for Convex Optimization. Journal of Machine Learning Research 17, 83 (2016), 1--5.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2009.02.002"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00175"},{"key":"e_1_3_2_1_13_1","unstructured":"Daniel S. Fava. 2018. Verification of Neural Networks via Linear Programming. https:\/\/github.com\/dfava\/readingclub\/wiki\/Verification-of-Neural-Networks-via-Linear-Programming.  Daniel S. Fava. 2018. Verification of Neural Networks via Linear Programming. https:\/\/github.com\/dfava\/readingclub\/wiki\/Verification-of-Neural-Networks-via-Linear-Programming."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813677"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Amir Globerson Choon-Hui Teo Alexander Smola Sam Roweis etal 2009. An adversarial view of covariate shift and a minimax approach. In Dataset shift in machine learning. MIT Press.  Amir Globerson Choon-Hui Teo Alexander Smola Sam Roweis et al. 2009. An adversarial view of covariate shift and a minimax approach. In Dataset shift in machine learning. MIT Press.","DOI":"10.7551\/mitpress\/9780262170055.003.0010"},{"key":"e_1_3_2_1_16_1","volume-title":"Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572","author":"Goodfellow Ian J","year":"2014","unstructured":"Ian J Goodfellow , Jonathon Shlens , and Christian Szegedy . 2014. Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572 ( 2014 ). Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014. Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572 (2014)."},{"key":"e_1_3_2_1_17_1","unstructured":"Matthias Hein and Maksym Andriushchenko. 2017. Formal guarantees on the robustness of a classifier against adversarial manipulation. In Advances in Neural Information Processing Systems. 2266--2276.  Matthias Hein and Maksym Andriushchenko. 2017. Formal guarantees on the robustness of a classifier against adversarial manipulation. In Advances in Neural Information Processing Systems. 2266--2276."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISRCS.2014.6900095"},{"key":"e_1_3_2_1_19_1","volume-title":"They Are Features. arXiv preprint arXiv:1905.02175","author":"Ilyas Andrew","year":"2019","unstructured":"Andrew Ilyas , Shibani Santurkar , Dimitris Tsipras , Logan Engstrom , Brandon Tran , and Aleksander Madry . 2019. Adversarial Examples Are Not Bugs , They Are Features. arXiv preprint arXiv:1905.02175 ( 2019 ). Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry. 2019. Adversarial Examples Are Not Bugs, They Are Features. arXiv preprint arXiv:1905.02175 (2019)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2825243"},{"volume-title":"Complexity of computer computations","author":"Karp Richard M","key":"e_1_3_2_1_21_1","unstructured":"Richard M Karp . 1972. Reducibility among combinatorial problems . In Complexity of computer computations . Springer , 85--103. Richard M Karp. 1972. Reducibility among combinatorial problems. In Complexity of computer computations. Springer, 85--103."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-63387-9_5"},{"key":"e_1_3_2_1_23_1","volume-title":"Failure Modes in Machine Learning Systems. arXiv preprint arXiv:1911.11034","author":"Siva Kumar Ram Shankar","year":"2019","unstructured":"Ram Shankar Siva Kumar , David O Brien , Kendra Albert , Salom\u00e9 Vilj\u00f6en , and Jeffrey Snover . 2019. Failure Modes in Machine Learning Systems. arXiv preprint arXiv:1911.11034 ( 2019 ). Ram Shankar Siva Kumar, David O Brien, Kendra Albert, Salom\u00e9 Vilj\u00f6en, and Jeffrey Snover. 2019. Failure Modes in Machine Learning Systems. arXiv preprint arXiv:1911.11034 (2019)."},{"key":"e_1_3_2_1_24_1","volume-title":"Certified robustness to adversarial examples with differential privacy. arXiv preprint arXiv:1802.03471","author":"Lecuyer Mathias","year":"2018","unstructured":"Mathias Lecuyer , Vaggelis Atlidakis , Roxana Geambasu , Daniel Hsu , and Suman Jana . 2018. Certified robustness to adversarial examples with differential privacy. arXiv preprint arXiv:1802.03471 ( 2018 ). Mathias Lecuyer, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, and Suman Jana. 2018. Certified robustness to adversarial examples with differential privacy. arXiv preprint arXiv:1802.03471 (2018)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_23"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2015.2397431"},{"key":"e_1_3_2_1_27_1","unstructured":"Gurobi Optimization LLC. 2019. Gurobi Optimizer Reference Manual. http:\/\/www.gurobi.com  Gurobi Optimization LLC. 2019. Gurobi Optimizer Reference Manual. http:\/\/www.gurobi.com"},{"key":"e_1_3_2_1_28_1","volume-title":"Towards deep learning models resistant to adversarial attacks. arXiv preprint arXiv:1706.06083","author":"Madry Aleksander","year":"2017","unstructured":"Aleksander Madry , Aleksandar Makelov , Ludwig Schmidt , Dimitris Tsipras , and Adrian Vladu . 2017. Towards deep learning models resistant to adversarial attacks. arXiv preprint arXiv:1706.06083 ( 2017 ). Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. 2017. Towards deep learning models resistant to adversarial attacks. arXiv preprint arXiv:1706.06083 (2017)."},{"key":"e_1_3_2_1_29_1","volume-title":"Security tip (ST04-015): understanding denial-of-service attacks. National Cyber Alert System","author":"McDowell M","year":"2004","unstructured":"M McDowell . 2004. Security tip (ST04-015): understanding denial-of-service attacks. National Cyber Alert System ( 2004 ). M McDowell. 2004. Security tip (ST04-015): understanding denial-of-service attacks. National Cyber Alert System (2004)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISGT.2019.8791598"},{"volume-title":"Numerical optimization","author":"Nocedal Jorge","key":"e_1_3_2_1_31_1","unstructured":"Jorge Nocedal and Stephen Wright . 2006. Numerical optimization . Springer Science & Business Media . Jorge Nocedal and Stephen Wright. 2006. Numerical optimization. Springer Science & Business Media."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2711565"},{"key":"e_1_3_2_1_33_1","volume-title":"Transferability in machine learning: from phenomena to black-box attacks using adversarial samples. arXiv preprint arXiv:1605.07277","author":"Papernot Nicolas","year":"2016","unstructured":"Nicolas Papernot , Patrick McDaniel , and Ian Goodfellow . 2016. Transferability in machine learning: from phenomena to black-box attacks using adversarial samples. arXiv preprint arXiv:1605.07277 ( 2016 ). Nicolas Papernot, Patrick McDaniel, and Ian Goodfellow. 2016. Transferability in machine learning: from phenomena to black-box attacks using adversarial samples. arXiv preprint arXiv:1605.07277 (2016)."},{"key":"e_1_3_2_1_34_1","volume-title":"Learning algorithms via neural logic networks. arXiv preprint arXiv:1904.01554","author":"Payani Ali","year":"2019","unstructured":"Ali Payani and Faramarz Fekri . 2019. Learning algorithms via neural logic networks. arXiv preprint arXiv:1904.01554 ( 2019 ). Ali Payani and Faramarz Fekri. 2019. Learning algorithms via neural logic networks. arXiv preprint arXiv:1904.01554 (2019)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"volume-title":"Dataset shift in machine learning","author":"Quionero-Candela Joaquin","key":"e_1_3_2_1_36_1","unstructured":"Joaquin Quionero-Candela , Masashi Sugiyama , Anton Schwaighofer , and Neil D Lawrence . 2009. Dataset shift in machine learning . The MIT Press . Joaquin Quionero-Candela, Masashi Sugiyama, Anton Schwaighofer, and Neil D Lawrence. 2009. Dataset shift in machine learning. The MIT Press."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/61.997911"},{"key":"e_1_3_2_1_38_1","first-page":"311","article-title":"Bundle methods for regularized risk minimization","author":"Teo Choon Hui","year":"2010","unstructured":"Choon Hui Teo , SVN Vishwanthan , Alex J Smola , and Quoc V Le . 2010 . Bundle methods for regularized risk minimization . Journal of Machine Learning Research 11 , Jan (2010), 311 -- 365 . Choon Hui Teo, SVN Vishwanthan, Alex J Smola, and Quoc V Le. 2010. Bundle methods for regularized risk minimization. Journal of Machine Learning Research 11, Jan (2010), 311--365.","journal-title":"Journal of Machine Learning Research 11"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.NEUCOM.2019.01.038"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2013.2272276"},{"key":"e_1_3_2_1_41_1","unstructured":"Guido Van Rossum and Fred L Drake  Jr. 1995. Python tutorial. Centrum voor Wiskunde en Informatica Amsterdam The Netherlands.  Guido Van Rossum and Fred L Drake Jr. 1995. Python tutorial. Centrum voor Wiskunde en Informatica Amsterdam The Netherlands."},{"key":"e_1_3_2_1_42_1","volume-title":"Evaluating the robustness of neural networks: An extreme value theory approach. arXiv preprint arXiv:1801.10578","author":"Weng Tsui-Wei","year":"2018","unstructured":"Tsui-Wei Weng , Huan Zhang , Pin-Yu Chen , Jinfeng Yi , Dong Su , Yupeng Gao , Cho-Jui Hsieh , and Luca Daniel . 2018. Evaluating the robustness of neural networks: An extreme value theory approach. arXiv preprint arXiv:1801.10578 ( 2018 ). Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, and Luca Daniel. 2018. Evaluating the robustness of neural networks: An extreme value theory approach. arXiv preprint arXiv:1801.10578 (2018)."},{"volume-title":"Logic and Integer Programming","author":"Williams H Paul","key":"e_1_3_2_1_43_1","unstructured":"H Paul Williams . 2009. Integer programming . In Logic and Integer Programming . Springer , 25--70. H Paul Williams. 2009. Integer programming. In Logic and Integer Programming. Springer, 25--70."},{"key":"e_1_3_2_1_44_1","volume-title":"Yuille","author":"Xie Cihang","year":"2017","unstructured":"Cihang Xie , Jianyu Wang , Zhishuai Zhang , Zhou Ren , and Alan L . Yuille . 2017 . Mitigating adversarial effects through randomization. CoRR abs\/1711.01991 (2017). arXiv:1711.01991 http:\/\/arxiv.org\/abs\/1711.01991 Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, and Alan L. Yuille. 2017. Mitigating adversarial effects through randomization. CoRR abs\/1711.01991 (2017). arXiv:1711.01991 http:\/\/arxiv.org\/abs\/1711.01991"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140449"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134052"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/iThings\/CPSCom.2011.34"}],"event":{"name":"HotSoS '20: Hot Topics in the Science of Security","acronym":"HotSoS '20","location":"Lawrence Kansas"},"container-title":["Proceedings of the 7th Symposium on Hot Topics in the Science of Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3384217.3385616","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3384217.3385616","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3384217.3385616","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3384217.3385616","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:03:23Z","timestamp":1750197803000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3384217.3385616"}},"subtitle":["adversarial training of power systems against denial-of-service attacks"],"short-title":[],"issued":{"date-parts":[[2020,9,21]]},"references-count":47,"alternative-id":["10.1145\/3384217.3385616","10.1145\/3384217"],"URL":"https:\/\/doi.org\/10.1145\/3384217.3385616","relation":{},"subject":[],"published":{"date-parts":[[2020,9,21]]},"assertion":[{"value":"2020-09-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}