{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T10:13:06Z","timestamp":1730283186465,"version":"3.28.0"},"reference-count":27,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,10]]},"DOI":"10.1109\/milcom.2018.8599715","type":"proceedings-article","created":{"date-parts":[[2019,1,3]],"date-time":"2019-01-03T18:10:39Z","timestamp":1546539039000},"page":"425-430","source":"Crossref","is-referenced-by-count":6,"title":["Enablers of Adversarial Attacks in Machine Learning"],"prefix":"10.1109","author":[{"given":"Rauf","family":"Izmailov","sequence":"first","affiliation":[]},{"given":"Shridatt","family":"Sugrim","sequence":"additional","affiliation":[]},{"given":"Ritu","family":"Chadha","sequence":"additional","affiliation":[]},{"given":"Patrick","family":"McDaniel","sequence":"additional","affiliation":[]},{"given":"Ananthram","family":"Swami","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","article-title":"Practical evasion of a learning-based classifier: a case study","author":"srndic","year":"2014","journal-title":"IEEE Symposium on Security and Privacy"},{"key":"ref11","article-title":"Evasion and hardening of tree ensemble classifiers","author":"kantchelian","year":"2015","journal-title":"ArXiv pre-print"},{"key":"ref12","first-page":"2087172095","article-title":"Feature cross-substitution in adversarial classification","author":"li","year":"0","journal-title":"Proceedings of the 27th International Conference on Neural Information Processing Systems NIPS&#x2019; 14"},{"key":"ref13","article-title":"A general retraining framework for scalable adversarial classification","author":"li","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref14","article-title":"The space of transferable adversarial examples","author":"tramer","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref15","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2014","journal-title":"ArXiv Preprint"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"journal-title":"Statistical Learning Theory Wiley Interscience","year":"1998","author":"vapnik","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262017091.001.0001"},{"key":"ref4","article-title":"Transferability in machine learning: from phenomena to black-box attacks using adversarial samples","author":"papernot","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCN.2017.8038523"},{"key":"ref3","first-page":"1293171332","article-title":"Query strategies for evading convex-inducing classifiers","volume":"13","author":"nelson","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref6","article-title":"DeepFool: a simple and accurate method to fool deep neural networks","author":"moosavi-dezfooli","year":"2015","journal-title":"ArXiv Preprint"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"key":"ref8","article-title":"Adversarial examples in the physical world","author":"kurakin","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.57"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978392"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40994-3_25"},{"journal-title":"Dataset Shift in Machine Learning","year":"2008","key":"ref20"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"ref21","article-title":"Scikit-learn: machine learning in Python","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref23","article-title":"cleverhans v1.0.0: an adversarial machine learning library","author":"papernot","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.istr.2009.03.003"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3233\/JCS-2010-0410"}],"event":{"name":"MILCOM 2018 - IEEE Military Communications Conference","start":{"date-parts":[[2018,10,29]]},"location":"Los Angeles, CA","end":{"date-parts":[[2018,10,31]]}},"container-title":["MILCOM 2018 - 2018 IEEE Military Communications Conference (MILCOM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8580348\/8599678\/08599715.pdf?arnumber=8599715","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T20:21:36Z","timestamp":1643142096000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8599715\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/milcom.2018.8599715","relation":{},"subject":[],"published":{"date-parts":[[2018,10]]}}}