{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T17:11:33Z","timestamp":1790183493426,"version":"4.1.0"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"DAPRA GARD"},{"name":"JP Morgan Chase"},{"name":"AFOSR MURI program"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,11,3]]},"DOI":"10.1145\/3490354.3494367","type":"proceedings-article","created":{"date-parts":[[2022,5,5]],"date-time":"2022-05-05T03:50:06Z","timestamp":1651722606000},"page":"1-9","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["Adversarial attacks on machine learning systems for high-frequency trading"],"prefix":"10.1145","author":[{"given":"Micah","family":"Goldblum","sequence":"first","affiliation":[{"name":"University of Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Avi","family":"Schwarzschild","sequence":"additional","affiliation":[{"name":"University of Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ankit","family":"Patel","sequence":"additional","affiliation":[{"name":"Rice University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tom","family":"Goldstein","sequence":"additional","affiliation":[{"name":"University of Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,5,4]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2016.04.007"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.21314\/JOR.2001.041"},{"key":"e_1_3_2_1_3_1","volume-title":"Generating natural language adversarial examples. arXiv preprint arXiv:1804.07998","author":"Alzantot Moustafa","year":"2018","unstructured":"Moustafa Alzantot , Yash Sharma , Ahmed Elgohary , Bo-Jhang Ho , Mani Srivastava , and Kai-Wei Chang . 2018. Generating natural language adversarial examples. arXiv preprint arXiv:1804.07998 ( 2018 ). Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang. 2018. Generating natural language adversarial examples. arXiv preprint arXiv:1804.07998 (2018)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10551-012-1559-0"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-42297-8_40"},{"key":"e_1_3_2_1_6_1","volume-title":"We're all high frequency traders now. Credit Suisse Market Structure White Paper","author":"Avramovic A","year":"2017","unstructured":"A Avramovic , V Lin , and M Krishnan . 2017. We're all high frequency traders now. Credit Suisse Market Structure White Paper ( 2017 ). A Avramovic, V Lin, and M Krishnan. 2017. We're all high frequency traders now. Credit Suisse Market Structure White Paper (2017)."},{"key":"e_1_3_2_1_7_1","first-page":"167","article-title":"Empirical analysis of ARMA-GARCH models in market risk estimation on high-frequency US data","volume":"17","author":"Beck Alexander","year":"2013","unstructured":"Alexander Beck , Young Shin Aaron Kim , Svetlozar Rachev , Michael Feindt , and Frank Fabozzi . 2013 . Empirical analysis of ARMA-GARCH models in market risk estimation on high-frequency US data . Studies in Nonlinear Dynamics and Econometrics 17 , 2 (2013), 167 -- 177 . Alexander Beck, Young Shin Aaron Kim, Svetlozar Rachev, Michael Feindt, and Frank Fabozzi. 2013. Empirical analysis of ARMA-GARCH models in market risk estimation on high-frequency US data. Studies in Nonlinear Dynamics and Econometrics 17, 2 (2013), 167--177.","journal-title":"Studies in Nonlinear Dynamics and Econometrics"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2010.08.008"},{"key":"e_1_3_2_1_9_1","volume-title":"Fairness in machine learning: Lessons from political philosophy. arXiv preprint arXiv:1712.03586","author":"Binns Reuben","year":"2017","unstructured":"Reuben Binns . 2017. Fairness in machine learning: Lessons from political philosophy. arXiv preprint arXiv:1712.03586 ( 2017 ). Reuben Binns. 2017. Fairness in machine learning: Lessons from political philosophy. arXiv preprint arXiv:1712.03586 (2017)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/for.2585"},{"key":"e_1_3_2_1_11_1","volume-title":"Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency. arXiv preprint arXiv:1908.08168","author":"Byrd David","year":"2019","unstructured":"David Byrd and Tucker Hybinette Balch . 2019. Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency. arXiv preprint arXiv:1908.08168 ( 2019 ). David Byrd and Tucker Hybinette Balch. 2019. Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency. arXiv preprint arXiv:1908.08168 (2019)."},{"key":"e_1_3_2_1_12_1","volume-title":"WITCHcraft: Efficient PGD attacks with random step size. arXiv preprint arXiv:1911.07989","author":"Chiang Ping-Yeh","year":"2019","unstructured":"Ping-Yeh Chiang , Jonas Geiping , Micah Goldblum , Tom Goldstein , Renkun Ni , Steven Reich , and Ali Shafahi . 2019. WITCHcraft: Efficient PGD attacks with random step size. arXiv preprint arXiv:1911.07989 ( 2019 ). Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, and Ali Shafahi. 2019. WITCHcraft: Efficient PGD attacks with random step size. arXiv preprint arXiv:1911.07989 (2019)."},{"key":"e_1_3_2_1_13_1","volume-title":"Trading via Image Classification. arXiv preprint arXiv:1907.10046","author":"Cohen Naftali","year":"2019","unstructured":"Naftali Cohen , Tucker Balch , and Manuela Veloso . 2019. Trading via Image Classification. arXiv preprint arXiv:1907.10046 ( 2019 ). Naftali Cohen, Tucker Balch, and Manuela Veloso. 2019. Trading via Image Classification. arXiv preprint arXiv:1907.10046 (2019)."},{"key":"e_1_3_2_1_14_1","volume-title":"Adversarial attack on graph structured data. arXiv preprint arXiv:1806.02371","author":"Dai Hanjun","year":"2018","unstructured":"Hanjun Dai , Hui Li , Tian Tian , Xin Huang , Lin Wang , Jun Zhu , and Le Song . 2018. Adversarial attack on graph structured data. arXiv preprint arXiv:1806.02371 ( 2018 ). Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, and Le Song. 2018. Adversarial attack on graph structured data. arXiv preprint arXiv:1806.02371 (2018)."},{"key":"e_1_3_2_1_15_1","volume-title":"Advances in financial machine learning","author":"De Prado Marcos Lopez","unstructured":"Marcos Lopez De Prado . 2018. Advances in financial machine learning . John Wiley & Sons . Marcos Lopez De Prado. 2018. Advances in financial machine learning. John Wiley & Sons."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2017.08.018"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00175"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-6261.2010.01624.x"},{"key":"e_1_3_2_1_19_1","volume-title":"The Problem With Prosecuting Spoofing. The New York Times","author":"Henning Peter J.","year":"2018","unstructured":"Peter J. Henning . 2018. The Problem With Prosecuting Spoofing. The New York Times ( 2018 ). Peter J. Henning. 2018. The Problem With Prosecuting Spoofing. The New York Times (2018)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_21_1","volume-title":"LOBSTER: Limit order book reconstruction system. Available at SSRN 1977207","author":"Huang Ruihong","year":"2011","unstructured":"Ruihong Huang and Tomas Polak . 2011 . LOBSTER: Limit order book reconstruction system. Available at SSRN 1977207 (2011). Ruihong Huang and Tomas Polak. 2011. LOBSTER: Limit order book reconstruction system. Available at SSRN 1977207 (2011)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1080\/14697688.2015.1032546"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1111\/jofi.12498"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1080\/17521440.2017.1336397"},{"key":"e_1_3_2_1_25_1","unstructured":"Wolters Kluwer. 2020. The Nasdaq Stock Market LLC Rules. http:\/\/nasdaq.cchwallstreet.com\/ (2020).  Wolters Kluwer. 2020. The Nasdaq Stock Market LLC Rules. http:\/\/nasdaq.cchwallstreet.com\/ (2020)."},{"key":"e_1_3_2_1_26_1","volume-title":"Adversarial examples in the physical world. arXiv preprint arXiv:1607.02533","author":"Kurakin Alexey","year":"2016","unstructured":"Alexey Kurakin , Ian Goodfellow , and Samy Bengio . 2016. Adversarial examples in the physical world. arXiv preprint arXiv:1607.02533 ( 2016 ). Alexey Kurakin, Ian Goodfellow, and Samy Bengio. 2016. Adversarial examples in the physical world. arXiv preprint arXiv:1607.02533 (2016)."},{"key":"e_1_3_2_1_27_1","volume-title":"Robo Advisors: Online Financial Advisors That Fit in Your Pocket. Business Insider Magazine","author":"Meola Andrew","year":"2017","unstructured":"Andrew Meola . 2017 . Robo Advisors: Online Financial Advisors That Fit in Your Pocket. Business Insider Magazine (2017). Andrew Meola. 2017. Robo Advisors: Online Financial Advisors That Fit in Your Pocket. Business Insider Magazine (2017)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.17"},{"key":"e_1_3_2_1_29_1","volume-title":"Putting Robo Advisors to the Test. The Wall Street Journal","author":"Moyer Liz","year":"2015","unstructured":"Liz Moyer . 2015. Putting Robo Advisors to the Test. The Wall Street Journal ( 2015 ). Liz Moyer. 2015. Putting Robo Advisors to the Test. The Wall Street Journal (2015)."},{"key":"e_1_3_2_1_30_1","unstructured":"MultiCharts. 2018. Limit Order Execution Assumptions. https:\/\/www.multicharts.com\/trading-software\/index.php\/Limit_Order_Execution_Assumptions  MultiCharts. 2018. Limit Order Execution Assumptions. https:\/\/www.multicharts.com\/trading-software\/index.php\/Limit_Order_Execution_Assumptions"},{"key":"e_1_3_2_1_31_1","volume-title":"Technical analysis of the financial markets: A comprehensive guide to trading methods and applications","author":"Murphy John J","unstructured":"John J Murphy . 1999. Technical analysis of the financial markets: A comprehensive guide to trading methods and applications . Penguin . John J Murphy. 1999. Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. Penguin."},{"key":"e_1_3_2_1_32_1","volume-title":"Efficiently inefficient: how smart money invests and market prices are determined","author":"Pedersen Lasse Heje","unstructured":"Lasse Heje Pedersen . 2019. Efficiently inefficient: how smart money invests and market prices are determined . Princeton University Press . Lasse Heje Pedersen. 2019. Efficiently inefficient: how smart money invests and market prices are determined. Princeton University Press."},{"key":"e_1_3_2_1_33_1","volume-title":"Manjeevan Seera, Chee Peng Lim, and Asoke K Nandi.","author":"Randhawa Kuldeep","year":"2018","unstructured":"Kuldeep Randhawa , Chu Kiong Loo , Manjeevan Seera, Chee Peng Lim, and Asoke K Nandi. 2018 . Credit card fraud detection using AdaBoost and majority voting. IEEE access 6 (2018), 14277--14284. Kuldeep Randhawa, Chu Kiong Loo, Manjeevan Seera, Chee Peng Lim, and Asoke K Nandi. 2018. Credit card fraud detection using AdaBoost and majority voting. IEEE access 6 (2018), 14277--14284."},{"key":"e_1_3_2_1_34_1","volume-title":"Adversarial attacks on copyright detection systems. arXiv preprint arXiv:1906.07153","author":"Saadatpanah Parsa","year":"2019","unstructured":"Parsa Saadatpanah , Ali Shafahi , and Tom Goldstein . 2019. Adversarial attacks on copyright detection systems. arXiv preprint arXiv:1906.07153 ( 2019 ). Parsa Saadatpanah, Ali Shafahi, and Tom Goldstein. 2019. Adversarial attacks on copyright detection systems. arXiv preprint arXiv:1906.07153 (2019)."},{"key":"e_1_3_2_1_35_1","first-page":"383","article-title":"Dodd-Frank and the Spoofing Prohibition in Commodities Markets","author":"Sar Meric","year":"2017","unstructured":"Meric Sar . 2017 . Dodd-Frank and the Spoofing Prohibition in Commodities Markets . Fordham J. Corp. & Fin. L. 22 (2017), 383 . Meric Sar. 2017. Dodd-Frank and the Spoofing Prohibition in Commodities Markets. Fordham J. Corp. & Fin. L. 22 (2017), 383.","journal-title":"Fordham J. Corp. & Fin."},{"key":"e_1_3_2_1_36_1","volume-title":"Universal adversarial training. arXiv preprint arXiv:1811.11304","author":"Shafahi Ali","year":"2018","unstructured":"Ali Shafahi , Mahyar Najibi , Zheng Xu , John Dickerson , Larry S Davis , and Tom Goldstein . 2018. Universal adversarial training. arXiv preprint arXiv:1811.11304 ( 2018 ). Ali Shafahi, Mahyar Najibi, Zheng Xu, John Dickerson, Larry S Davis, and Tom Goldstein. 2018. Universal adversarial training. arXiv preprint arXiv:1811.11304 (2018)."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978392"},{"key":"e_1_3_2_1_38_1","volume-title":"Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199","author":"Szegedy Christian","year":"2013","unstructured":"Christian Szegedy , Wojciech Zaremba , Ilya Sutskever , Joan Bruna , Dumitru Erhan , Ian Goodfellow , and Rob Fergus . 2013. Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199 ( 2013 ). Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2013. Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199 (2013)."}],"event":{"name":"ICAIF'21: 2nd ACM International Conference on AI in Finance","location":"Virtual Event","acronym":"ICAIF'21","sponsor":["ACM Association for Computing Machinery"]},"container-title":["Proceedings of the Second ACM International Conference on AI in Finance"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490354.3494367","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3490354.3494367","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:42Z","timestamp":1750188642000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490354.3494367"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,3]]},"references-count":38,"alternative-id":["10.1145\/3490354.3494367","10.1145\/3490354"],"URL":"https:\/\/doi.org\/10.1145\/3490354.3494367","relation":{},"subject":[],"published":{"date-parts":[[2021,11,3]]},"assertion":[{"value":"2022-05-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}