{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T05:08:21Z","timestamp":1768280901566,"version":"3.49.0"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Recovery and Resilience Plan Ministry of University and Research (NRRP MUR) Program funded by European Union NextGenerationEU (EU\u2013NGEU) through the project SERICS","award":["PE00000014"],"award-info":[{"award-number":["PE00000014"]}]},{"name":"project Future Artificial Intelligence Research","award":["PE00000013"],"award-info":[{"award-number":["PE00000013"]}]},{"name":"European Research Council","award":["SLING 819789"],"award-info":[{"award-number":["SLING 819789"]}]},{"name":"European Commission through Horizon Europe","award":["ELIAS 101120237"],"award-info":[{"award-number":["ELIAS 101120237"]}]},{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","award":["FA8655-22-1-7034"],"award-info":[{"award-number":["FA8655-22-1-7034"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Education, University and Research through Fund for the Attraction of Excellent Researchers","award":["ML4IP R205T7J2KP"],"award-info":[{"award-number":["ML4IP R205T7J2KP"]}]},{"name":"France 2030 Support managed by the Agence Nationale de la Recherche","award":["ANR-23-PEIA-0004"],"award-info":[{"award-number":["ANR-23-PEIA-0004"]}]},{"name":"\u201cInfoAICert\u201d funded by the MUR Program \u201cFondo Italiano per le Scienze Applicate\u201d","award":["FISA-2023-00128"],"award-info":[{"award-number":["FISA-2023-00128"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/tifs.2025.3648867","type":"journal-article","created":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T18:23:11Z","timestamp":1766773391000},"page":"506-515","source":"Crossref","is-referenced-by-count":0,"title":["A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection"],"prefix":"10.1109","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3839-1429","authenticated-orcid":false,"given":"Marco","family":"Rando","sequence":"first","affiliation":[{"name":"LJAD, CNRS, Inria, Université Côte d’Azur, Nice, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5104-1476","authenticated-orcid":false,"given":"Luca","family":"Demetrio","sequence":"additional","affiliation":[{"name":"University of Genova, Genova, Italy"}]},{"given":"Lorenzo","family":"Rosasco","sequence":"additional","affiliation":[{"name":"MaLGa-DIBRIS, University of Genova, Genova, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4103-9190","authenticated-orcid":false,"given":"Fabio","family":"Roli","sequence":"additional","affiliation":[{"name":"University of Genova, Genova, Italy"}]}],"member":"263","reference":[{"key":"ref1","article-title":"EMBER: An open dataset for training static PE malware machine learning models","author":"Anderson","year":"2018","journal-title":"arXiv:1804.04637"},{"key":"ref2","article-title":"Malware detection by eating a whole exe","volume-title":"Proc. Workshops 32nd AAAI Conf. Artif. Intell.","author":"Raff"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3560830.3563726"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2019.102526"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3473039"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2021.3082330"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3433210.3453086"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3488932.3497768"},{"key":"ref9","first-page":"1","article-title":"Evading machine learning malware detection","volume-title":"Proc. Black Hat","author":"Anderson"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.23919\/EUSIPCO.2018.8553214"},{"key":"ref11","first-page":"36738","article-title":"An optimal structured zeroth-order algorithm for non-smooth optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Rando"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.07.023"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729392"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10208-015-9296-2"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10208-021-09513-z"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/BF00934819"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1137\/120880811"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2015.2409256"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3150\/21-BEJ1400"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-52156-5_2"},{"key":"ref21","article-title":"Secml-malware: Pentesting windows malware classifiers with adversarial EXEmples in Python","author":"Demetrio","year":"2021","journal-title":"arXiv:2104.12848"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1137\/19M1291832"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3427228.3427261"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/SP40000.2020.00073"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TrustCom\/BigDataSE.2019.00040"},{"issue":"52","key":"ref26","first-page":"1","article-title":"An optimal algorithm for bandit and zero-order convex optimization with two-point feedback","volume":"18","author":"Shamir","year":"2017","journal-title":"J. Mach. Learn. Res."},{"key":"ref27","article-title":"Stochastic zeroth order descent with structured directions","author":"Rando","year":"2022","journal-title":"arXiv:2206.05124"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-022-01866-9"},{"key":"ref29","first-page":"1193","article-title":"A zeroth-order block coordinate descent algorithm for huge-scale black-box optimization","volume-title":"Proc. 38th Int. Conf. Mach. Learn.","author":"Cai"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1137\/21M1392966"},{"key":"ref31","first-page":"970","article-title":"Structured evolution with compact architectures for scalable policy optimization","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","volume":"80","author":"Choromanski"},{"key":"ref32","article-title":"RobustBench: A standardized adversarial robustness benchmark","volume-title":"Proc. 35th Conf. Neural Inf. Process. Syst. Datasets Benchmarks Track","author":"Croce"},{"key":"ref33","first-page":"1163","article-title":"Adversarial training for raw-binary malware classifiers","volume-title":"Proc. 32nd USENIX Secur. Symp.","author":"Lucas"},{"key":"ref34","article-title":"RS-del: Edit distance robustness certificates for sequence classifiers via randomized deletion","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Huang"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3605764.3623914"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1137\/110831659"},{"key":"ref37","first-page":"26160","article-title":"Gradient-free methods for deterministic and stochastic nonsmooth nonconvex optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lin"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2011.09.043"},{"key":"ref39","first-page":"32","volume":"1","author":"Polyak","year":"1987","journal-title":"Introduction to Optimization"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/10206\/11313711\/11316492-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10206\/11313711\/11316492.pdf?arnumber=11316492","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T21:59:20Z","timestamp":1768255160000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11316492\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/tifs.2025.3648867","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}