{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T08:16:13Z","timestamp":1763367373905,"version":"3.28.0"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"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":[[2019,7]]},"DOI":"10.1109\/iolts.2019.8854425","type":"proceedings-article","created":{"date-parts":[[2019,10,4]],"date-time":"2019-10-04T00:27:48Z","timestamp":1570148868000},"page":"188-193","source":"Crossref","is-referenced-by-count":18,"title":["TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks"],"prefix":"10.1109","author":[{"given":"Faiq","family":"Khalid","sequence":"first","affiliation":[]},{"given":"Muhammad Abdullah","family":"Hanif","sequence":"additional","affiliation":[]},{"given":"Semeen","family":"Rehman","sequence":"additional","affiliation":[]},{"given":"Rehan","family":"Ahmed","sequence":"additional","affiliation":[]},{"given":"Muhammad","family":"Shafique","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref33","first-page":"99","article-title":"Adversarial examples in the physical world","author":"kurakin","year":"2018","journal-title":"AISS"},{"key":"ref32","first-page":"20","article-title":"Explaining and harnessing adversarial examples","volume":"1050","author":"goodfellow","year":"2015","journal-title":"Stat"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2016.7727230"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298640"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140448"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref34","article-title":"One pixel attack for fooling deep neural networks","author":"su","year":"2017","journal-title":"arXiv 1710 08864"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2018.00035"},{"key":"ref11","first-page":"2628","article-title":"Data poisoning attacks on multi-task relationship learning","author":"zhao","year":"2018","journal-title":"AAAI"},{"key":"ref12","article-title":"Data poisoning attacks against online learning","author":"wang","year":"2018","journal-title":"arXiv 1808 08994"},{"key":"ref13","article-title":"Poison frogs! targeted clean-label poisoning attacks on neural networks","author":"shafahi","year":"2018","journal-title":"arXiv 1804 00792"},{"key":"ref14","article-title":"Potrojan: powerful neural-level trojan designs in deep learning models","author":"zou et al","year":"2018","journal-title":"arXiv preprint arXiv 1802 03043"},{"key":"ref15","article-title":"Generic black-box end-to-end attack against rnns and other api calls based malware classifiers","author":"rosenberg","year":"2017","journal-title":"arXiv 1707 05970"},{"key":"ref16","article-title":"Adversarial examples in the physical world","author":"kurakin","year":"2016","journal-title":"arXiv 1607 02533"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/FIT.2018.00064"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2018.00057"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.2200\/S00861ED1V01Y201806AIM039"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2018.8342120"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2011.6033395"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2891969"},{"key":"ref6","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"NIPS"},{"journal-title":"Adversarial machine learning","year":"2018","author":"a d j","key":"ref29"},{"key":"ref5","article-title":"End to end learning for self-driving cars","author":"bojarski","year":"2016","journal-title":"arXiv 1604 07316 [cs]"},{"key":"ref8","first-page":"3520","article-title":"Certified defenses for data poisoning attacks","author":"steinhardt","year":"2017","journal-title":"NIPS"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref2","article-title":"Worldwide and regional internet of things (iot) 2014&#x2013;2020 forecast: A virtuous circle of proven value and demand","volume":"1","author":"lund","year":"2014","journal-title":"International Data Corporation (IDC) Tech Rep"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0184952"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tra.2016.10.013"},{"journal-title":"arXiv 1610 00768","article-title":"CleverHans v2. 0.0: an adversarial machine learning library","year":"2016","key":"ref20"},{"journal-title":"DATE","article-title":"FAdeML: understanding the impact of pre-processing noise filtering on adversarial machine learning","year":"2019","key":"ref22"},{"key":"ref21","article-title":"FAdeML: understanding the impact of pre-processing noise filtering on adversarial machine learning","author":"khalid","year":"2018","journal-title":"arXiv 1811 01444"},{"key":"ref24","article-title":"Badnets: Identifying vulnerabilities in the machine learning model supply chain","author":"gu","year":"2017","journal-title":"arXiv 1708 06733"},{"key":"ref23","article-title":"RED-Attack: Resource efficient decision based attack for machine learning","author":"khalid","year":"2019","journal-title":"arXiv preprint arXiv 1901 10258"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.58"},{"key":"ref25","article-title":"Intriguing properties of neural networks","author":"szegedy","year":"2013","journal-title":"arXiv 1312 6199"}],"event":{"name":"2019 IEEE 25th International Symposium on On-Line Testing And Robust System Design (IOLTS)","start":{"date-parts":[[2019,7,1]]},"location":"Rhodes, Greece","end":{"date-parts":[[2019,7,3]]}},"container-title":["2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design (IOLTS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8846168\/8854369\/08854425.pdf?arnumber=8854425","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T21:50:51Z","timestamp":1658094651000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8854425\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/iolts.2019.8854425","relation":{},"subject":[],"published":{"date-parts":[[2019,7]]}}}