{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T11:25:58Z","timestamp":1772450758510,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T00:00:00Z","timestamp":1604880000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"JST","award":["JPMJMI19B6"],"award-info":[{"award-number":["JPMJMI19B6"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,11,13]]},"DOI":"10.1145\/3411508.3421375","type":"proceedings-article","created":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T21:16:40Z","timestamp":1604351800000},"page":"117-127","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":38,"title":["Disabling Backdoor and Identifying Poison Data by using Knowledge Distillation in Backdoor Attacks on Deep Neural Networks"],"prefix":"10.1145","author":[{"given":"Kota","family":"Yoshida","sequence":"first","affiliation":[{"name":"Ritsumeikan University, Kusatsu, Japan"}]},{"given":"Takeshi","family":"Fujino","sequence":"additional","affiliation":[{"name":"Ritsumeikan University, Kusatsu, Japan"}]}],"member":"320","published-online":{"date-parts":[[2020,11,9]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering. arxiv","author":"Chen Bryant","year":"1811","unstructured":"Bryant Chen , Wilka Carvalho , Nathalie Baracaldo , Heiko Ludwig , Benjamin Edwards , Taesung Lee , Ian Molloy , and Biplav Srivastava . 2018. Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering. arxiv : 1811 .03728 [cs.LG] Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian Molloy, and Biplav Srivastava. 2018. Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering. arxiv: 1811.03728 [cs.LG]"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/647"},{"key":"e_1_3_2_1_3_1","volume-title":"Born Again Neural Networks. arxiv","author":"Furlanello Tommaso","year":"1805","unstructured":"Tommaso Furlanello , Zachary C. Lipton , Michael Tschannen , Laurent Itti , and Anima Anandkumar . 2018. Born Again Neural Networks. arxiv : 1805 .04770 [stat.ML] Tommaso Furlanello, Zachary C. Lipton, Michael Tschannen, Laurent Itti, and Anima Anandkumar. 2018. Born Again Neural Networks. arxiv: 1805.04770 [stat.ML]"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359790"},{"key":"e_1_3_2_1_5_1","unstructured":"Tianyu Gu Brendan Dolan-Gavitt and Siddharth Garg. 2017. BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain. arxiv: 1708.06733 [cs.CR]  Tianyu Gu Brendan Dolan-Gavitt and Siddharth Garg. 2017. BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain. arxiv: 1708.06733 [cs.CR]"},{"key":"e_1_3_2_1_6_1","unstructured":"Geoffrey Hinton Oriol Vinyals and Jeff Dean. 2015. Distilling the Knowledge in a Neural Network. arxiv: 1503.02531 [stat.ML]  Geoffrey Hinton Oriol Vinyals and Jeff Dean. 2015. Distilling the Knowledge in a Neural Network. arxiv: 1503.02531 [stat.ML]"},{"key":"e_1_3_2_1_7_1","unstructured":"Yann LeCun and Corinna Cortes. 2010. MNIST handwritten digit database. http:\/\/yann.lecun.com\/exdb\/mnist\/. (2010). http:\/\/yann.lecun.com\/exdb\/mnist\/  Yann LeCun and Corinna Cortes. 2010. MNIST handwritten digit database. http:\/\/yann.lecun.com\/exdb\/mnist\/. (2010). http:\/\/yann.lecun.com\/exdb\/mnist\/"},{"key":"e_1_3_2_1_8_1","volume-title":"Research in Attacks","author":"Liu Kang","unstructured":"Kang Liu , Brendan Dolan-Gavitt , and Siddharth Garg . 2018. Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks . In Research in Attacks , Intrusions, and Defenses, Michael Bailey, Thorsten Holz, Manolis Stamatogiannakis, and Sotiris Ioannidis (Eds.). Springer International Publishing , Cham , 273--294. Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg. 2018. Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks. In Research in Attacks, Intrusions, and Defenses, Michael Bailey, Thorsten Holz, Manolis Stamatogiannakis, and Sotiris Ioannidis (Eds.). Springer International Publishing, Cham, 273--294."},{"key":"e_1_3_2_1_9_1","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition. arxiv: 1409.1556 [cs.CV]  Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition. arxiv: 1409.1556 [cs.CV]"},{"key":"e_1_3_2_1_10_1","volume-title":"Exposing Backdoors in Robust Machine Learning Models. arxiv","author":"Soremekun Ezekiel","year":"2003","unstructured":"Ezekiel Soremekun , Sakshi Udeshi , and Sudipta Chattopadhyay . 2020. Exposing Backdoors in Robust Machine Learning Models. arxiv : 2003 .00865 [cs.CV] Ezekiel Soremekun, Sakshi Udeshi, and Sudipta Chattopadhyay. 2020. Exposing Backdoors in Robust Machine Learning Models. arxiv: 2003.00865 [cs.CV]"},{"key":"#cr-split#-e_1_3_2_1_11_1.1","doi-asserted-by":"crossref","unstructured":"J. Stallkamp M. Schlipsing J. Salmen and C. Igel. 2012. Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. Neural Networks 0 (2012) --. https:\/\/doi.org\/10.1016\/j.neunet.2012.02.016 10.1016\/j.neunet.2012.02.016","DOI":"10.1016\/j.neunet.2012.02.016"},{"key":"#cr-split#-e_1_3_2_1_11_1.2","doi-asserted-by":"crossref","unstructured":"J. Stallkamp M. Schlipsing J. Salmen and C. Igel. 2012. Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. Neural Networks 0 (2012) --. https:\/\/doi.org\/10.1016\/j.neunet.2012.02.016","DOI":"10.1016\/j.neunet.2012.02.016"},{"key":"e_1_3_2_1_12_1","volume-title":"Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks. In 2019 IEEE Symposium on Security and Privacy (SP). 707--723","author":"Wang B.","unstructured":"B. Wang , Y. Yao , S. Shan , H. Li , B. Viswanath , H. Zheng , and B. Y. Zhao . 2019 . Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks. In 2019 IEEE Symposium on Security and Privacy (SP). 707--723 . B. Wang, Y. Yao, S. Shan, H. Li, B. Viswanath, H. Zheng, and B. Y. Zhao. 2019. Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks. In 2019 IEEE Symposium on Security and Privacy (SP). 707--723."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.2299\/jsp.24.141"},{"key":"e_1_3_2_1_14_1","volume-title":"Deep Mutual Learning. 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (Jun 2018","author":"Zhang Ying","year":"2018","unstructured":"Ying Zhang , Tao Xiang , Timothy M. Hospedales , and Huchuan Lu . 2018 . Deep Mutual Learning. 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (Jun 2018 ). https:\/\/doi.org\/10.1109\/cvpr.2018.00454 10.1109\/cvpr.2018.00454 Ying Zhang, Tao Xiang, Timothy M. Hospedales, and Huchuan Lu. 2018. Deep Mutual Learning. 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (Jun 2018). https:\/\/doi.org\/10.1109\/cvpr.2018.00454"}],"event":{"name":"CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security","location":"Virtual Event USA","acronym":"CCS '20","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"]},"container-title":["Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3411508.3421375","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3411508.3421375","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:02:37Z","timestamp":1750197757000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3411508.3421375"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,9]]},"references-count":15,"alternative-id":["10.1145\/3411508.3421375","10.1145\/3411508"],"URL":"https:\/\/doi.org\/10.1145\/3411508.3421375","relation":{},"subject":[],"published":{"date-parts":[[2020,11,9]]},"assertion":[{"value":"2020-11-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}