{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T04:01:45Z","timestamp":1745640105708,"version":"3.40.4"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["62302458"],"award-info":[{"award-number":["62302458"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Foundation of He\u2019nan Educational Committee","award":["242102210060"],"award-info":[{"award-number":["242102210060"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,5,1]]},"DOI":"10.1109\/jiot.2024.3520642","type":"journal-article","created":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T19:34:22Z","timestamp":1734636862000},"page":"12267-12277","source":"Crossref","is-referenced-by-count":0,"title":["A New Data-Free Backdoor Removal Method via Adversarial Self-Knowledge Distillation"],"prefix":"10.1109","volume":"12","author":[{"given":"Xuexiang","family":"Li","sequence":"first","affiliation":[{"name":"School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, China"}]},{"given":"Yafei","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8477-0090","authenticated-orcid":false,"given":"Minglin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, China"}]},{"given":"Xu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Michigan Technological University, Houghton, MI, USA"}]},{"given":"Xianfu","family":"Chen","sequence":"additional","affiliation":[{"name":"Shenzhen CyberAray Network Technology Company Ltd, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6853-5878","authenticated-orcid":false,"given":"Celimuge","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Computer and Network Engineering, The University of Electro-Communications, Tokyo, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4974-6116","authenticated-orcid":false,"given":"Jie","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1109\/JIOT.2023.3268316"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1109\/ACCESS.2019.2909068"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/TEVC.2019.2890858"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/ICIP.2019.8802997"},{"key":"ref5","first-page":"3454","article-title":"Input-aware dynamic backdoor attack","volume-title":"Proc. 34th NeurIPS","author":"Nguyen"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/EuroSP53844.2022.00049"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1007\/978-3-030-58607-2_11"},{"key":"ref8","first-page":"1","article-title":"WaNet\u2014Imperceptible warping-based backdoor attack","volume-title":"Proc. ICLR","author":"Nguyen"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1109\/CVPR52688.2022.01465"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.14722\/ndss.2018.23291"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1109\/ICCV48922.2021.01616"},{"key":"ref12","article-title":"Label-consistent backdoor attacks","author":"Turner","year":"2019","journal-title":"arXiv:1912.02771"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1109\/JIOT.2024.3392772"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1109\/JIOT.2023.3237806"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/JIOT.2024.3368754"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1109\/TNNLS.2022.3182979"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1145\/3359789.3359790"},{"key":"ref18","article-title":"Detecting backdoor attacks on deep neural networks by activation clustering","author":"Chen","year":"2018","journal-title":"arXiv:1811.03728"},{"key":"ref19","first-page":"8011","article-title":"Spectral signatures in backdoor attacks","volume-title":"Proc. NeurIPS","author":"Tran"},{"key":"ref20","article-title":"Improved regularization of convolutional neural networks with cutout","author":"Devries","year":"2017","journal-title":"arXiv:1708.04552"},{"key":"ref21","article-title":"MaxUp: A simple way to improve generalization of neural network training","author":"Gong","year":"2020","journal-title":"arXiv:2002.09024"},{"key":"ref22","first-page":"1","article-title":"Robust anomaly detection and backdoor attack detection via differential privacy","volume-title":"Proc. ICLR","author":"Du"},{"key":"ref23","first-page":"8230","article-title":"Certified robustness to label-flipping attacks via randomized smoothing","volume-title":"Proc. ICML","author":"Rosenfeld"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1109\/SP.2019.00031"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.1007\/978-3-030-00470-5_13"},{"key":"ref26","first-page":"1","article-title":"Neural attention distillation: Erasing backdoor triggers from deep neural networks","volume-title":"Proc. ICLR","author":"Li"},{"key":"ref27","first-page":"16913","article-title":"Adversarial neuron pruning purifies backdoored deep models","volume-title":"Proc. 35th NeurIPS","author":"Wu"},{"key":"ref28","first-page":"1","article-title":"Adversarial unlearning of backdoors via implicit hypergradient","volume-title":"Proc. ICLR","author":"Zeng"},{"volume-title":"Learning Multiple Layers of Features From Tiny Images","year":"2009","author":"Krizhevsky","key":"ref29"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1007\/978-3-031-20065-6_11"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1145\/3579856.3582822"},{"key":"ref32","first-page":"33876","article-title":"Randomized channel shuffling: Minimal-overhead backdoor attack detection without clean datasets","volume-title":"Proc. 36th NeurIPS","author":"Cai"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/CVPR.2017.195"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1109\/CVPR.2017.634"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/ICASSP39728.2021.9414568"},{"doi-asserted-by":"publisher","key":"ref36","DOI":"10.1109\/NCC55593.2022.9806750"},{"key":"ref37","first-page":"13199","article-title":"Revisiting data-free knowledge distillation with poisoned teachers","volume-title":"Proc. 40th ICML","author":"Hong"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1109\/ICCV.2019.00361"},{"doi-asserted-by":"publisher","key":"ref39","DOI":"10.1109\/CVPR42600.2020.00874"},{"key":"ref40","article-title":"Data-free adversarial distillation","author":"Fang","year":"2020","journal-title":"arXiv:1912.11006"},{"doi-asserted-by":"publisher","key":"ref41","DOI":"10.1109\/CVPR.2016.90"},{"doi-asserted-by":"publisher","key":"ref42","DOI":"10.1007\/978-3-319-46493-0_38"},{"doi-asserted-by":"publisher","key":"ref43","DOI":"10.1016\/j.neunet.2012.02.016"},{"key":"ref44","article-title":"Targeted backdoor attacks on deep learning systems using data poisoning","author":"Chen","year":"2017","journal-title":"arXiv:1712.05526"},{"key":"ref45","first-page":"10546","article-title":"BackdoorBench: A comprehensive benchmark of backdoor learning","volume-title":"Proc. 36th NeurIPS","author":"Wu"},{"doi-asserted-by":"publisher","key":"ref46","DOI":"10.1109\/ICCV.2017.74"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/10975848\/10810368.pdf?arnumber=10810368","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T05:06:02Z","timestamp":1745557562000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10810368\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,1]]},"references-count":46,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2024.3520642","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"type":"electronic","value":"2327-4662"},{"type":"electronic","value":"2372-2541"}],"subject":[],"published":{"date-parts":[[2025,5,1]]}}}