{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T16:31:54Z","timestamp":1747153914364,"version":"3.28.0"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T00:00:00Z","timestamp":1651449600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T00:00:00Z","timestamp":1651449600000},"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":[[2022,5,2]]},"DOI":"10.1109\/infocomwkshps54753.2022.9798161","type":"proceedings-article","created":{"date-parts":[[2022,6,20]],"date-time":"2022-06-20T21:18:54Z","timestamp":1655759934000},"page":"1-6","source":"Crossref","is-referenced-by-count":10,"title":["An Investigation on Fragility of Machine Learning Classifiers in Android Malware Detection"],"prefix":"10.1109","author":[{"given":"Husnain","family":"Rafiq","sequence":"first","affiliation":[{"name":"Northumbria University,Department of Computer and Information Sciences,Newcastle,United Kingdom"}]},{"given":"Nauman","family":"Aslam","sequence":"additional","affiliation":[{"name":"Northumbria University,Department of Computer and Information Sciences,Newcastle,United Kingdom"}]},{"given":"Biju","family":"Issac","sequence":"additional","affiliation":[{"name":"Northumbria University,Department of Computer and Information Sciences,Newcastle,United Kingdom"}]},{"given":"Rizwan Hamid","family":"Randhawa","sequence":"additional","affiliation":[{"name":"Northumbria University,Department of Computer and Information Sciences,Newcastle,United Kingdom"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.11.032"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3162625"},{"key":"ref12","article-title":"Generating adversarial malware examples for blackbox attacks based on gan","author":"hu","year":"2017","journal-title":"arXiv preprint arXiv 1702 05983"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-62223-7_2"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2019.2906120"},{"key":"ref15","first-page":"101","article-title":"Deep convolutional generative adversarial networks for intent-based dynamic behavior capture","volume":"7","author":"jan","year":"2018","journal-title":"International Journal of Engineering & Technology"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-020-03083-5"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2014.23247"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3003571"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/522"},{"key":"ref4","article-title":"Deceiving end-to-end deep learning malware detectors using adversarial examples","author":"kreuk","year":"2018","journal-title":"arXiv preprint arXiv 1802 04102"},{"key":"ref3","article-title":"Sok: Arms race in adversarial malware detection","author":"li","year":"2020","journal-title":"arXiv preprint arXiv 2005 11084"},{"key":"ref6","article-title":"When the guard failed the droid: A case study of android malware","author":"berger","year":"2020","journal-title":"arXiv preprint arXiv 2003 14412"},{"key":"ref5","article-title":"Adversarial perturbations against deep neural networks for malware classification","author":"grosse","year":"2016","journal-title":"arXiv preprint arXiv 1606 04435"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-16549-3_60"},{"key":"ref7","first-page":"82","article-title":"Adam: an automatic and extensible platform to stress test android anti-virus systems","author":"zheng","year":"2012","journal-title":"Detection of Intrusions and Malware and Vulnerability Assessment"},{"key":"ref2","first-page":"253","article-title":"Gotcha-sly malware! scorpion a metagraph2vec based malware detection system","author":"fan","year":"2018","journal-title":"ACM SIGKDD International Conference on Knowledge Discovery and Data Mining"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/737"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2897845.2897856"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3083421"},{"key":"ref21","article-title":"Revisiting classifier two-sample tests","author":"lopez-paz","year":"2016","journal-title":"arXiv preprint arXiv 1610 06088"}],"event":{"name":"IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","start":{"date-parts":[[2022,5,2]]},"location":"New York, NY, USA","end":{"date-parts":[[2022,5,5]]}},"container-title":["IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9797887\/9797888\/09798161.pdf?arnumber=9798161","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,11]],"date-time":"2022-07-11T20:01:23Z","timestamp":1657569683000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9798161\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,2]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/infocomwkshps54753.2022.9798161","relation":{},"subject":[],"published":{"date-parts":[[2022,5,2]]}}}