{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T06:44:35Z","timestamp":1773384275618,"version":"3.50.1"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,18]]},"DOI":"10.1109\/ijcnn52387.2021.9533551","type":"proceedings-article","created":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T17:27:41Z","timestamp":1632158861000},"page":"1-8","source":"Crossref","is-referenced-by-count":1,"title":["Linear Program Powered Attack"],"prefix":"10.1109","author":[{"given":"Ismaila","family":"SECK","sequence":"first","affiliation":[{"name":"Normandie Univ, INSA Rouen UNIROUEN, UNIHAVRE, LITIS,Saint-Etienne-du-Rouvray,France"}]},{"given":"Gaelle","family":"LOOSLI","sequence":"additional","affiliation":[{"name":"PobRun,Brioude,France"}]},{"given":"Stephane","family":"CANU","sequence":"additional","affiliation":[{"name":"Normandie Univ, INSA Rouen UNIROUEN, UNIHAVRE, LITIS,Saint-Etienne-du-Rouvray,France"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01213-0"},{"key":"ref11","author":"zombori","year":"2020","journal-title":"Fooling a Complete Neural Network Verifier"},{"key":"ref12","article-title":"Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples","author":"athalye","year":"0","journal-title":"Proceedings of the 35th International Conference on Machine Learning"},{"key":"ref13","first-page":"4790","article-title":"A Unified View of Piecewise Linear Neural Network Verification","volume":"31","author":"bunel","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref14","article-title":"Understanding Deep Neural Networks with Rectified Linear Units","author":"arora","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref15","first-page":"2087","article-title":"Feature Cross-Substitution in Adversarial Classification","volume":"27","author":"li","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref16","article-title":"Rearchitecting Classification Frameworks For Increased Robustness","author":"chandrasekaran","year":"2019","journal-title":"ArXiv"},{"key":"ref17","author":"wolsey","year":"1999","journal-title":"Integer and Combinatorial Optimization"},{"key":"ref18","first-page":"4558","article-title":"Bounding and Counting Linear Regions of Deep Neural Networks","author":"serra","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref19","article-title":"Adversarial examples in the physical world","author":"kurakin","year":"2017","journal-title":"ArXiv"},{"key":"ref4","author":"tjeng","year":"2018","journal-title":"Evaluating robustness of neural networks with mixed integer programming"},{"key":"ref3","article-title":"Relu-plex: An Efficient SMT Solver for Verifying Deep Neural Networks","author":"katz","year":"2017","journal-title":"ArXiv"},{"key":"ref6","article-title":"Towards Deep Learning Models Resistant to Adversarial Attacks","author":"madry","year":"2019","journal-title":"ArXiv"},{"key":"ref5","first-page":"2613","article-title":"Measuring Neural Net Robustness with Constraints","author":"bastani","year":"2016","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref7","article-title":"Accurate, reliable and fast robustness evaluation","author":"brendel","year":"0","journal-title":"ArXiv"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"key":"ref1","first-page":"20","article-title":"Explaining and Harnessing Adversarial Examples","volume":"1050","author":"goodfellow","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref9","article-title":"A randomized gradient-free attack on ReLU networks","author":"croce","year":"2018","journal-title":"ArXiv"},{"key":"ref20","first-page":"9832","article-title":"A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks","volume":"32","author":"salman","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref22","first-page":"2057","article-title":"Provable Robustness of ReLU networks via Maximization of Linear Regions","author":"croce","year":"0","journal-title":"International Conference on Artificial Intelligence and Statistics"},{"key":"ref21","first-page":"5283","article-title":"Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope","author":"wong","year":"0","journal-title":"International Conference on Machine Learning"}],"event":{"name":"2021 International Joint Conference on Neural Networks (IJCNN)","location":"Shenzhen, China","start":{"date-parts":[[2021,7,18]]},"end":{"date-parts":[[2021,7,22]]}},"container-title":["2021 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9533266\/9533267\/09533551.pdf?arnumber=9533551","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,2]],"date-time":"2022-08-02T19:32:57Z","timestamp":1659468777000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9533551\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,18]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/ijcnn52387.2021.9533551","relation":{},"subject":[],"published":{"date-parts":[[2021,7,18]]}}}