{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T19:03:28Z","timestamp":1762196608480,"version":"build-2065373602"},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T00:00:00Z","timestamp":1752624000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T00:00:00Z","timestamp":1752624000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006190","name":"Research and Development","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006190","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,7,16]]},"DOI":"10.1109\/qrs-c65679.2025.00072","type":"proceedings-article","created":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T17:10:04Z","timestamp":1761930604000},"page":"540-549","source":"Crossref","is-referenced-by-count":0,"title":["A Defense Scheme of Backdoor Attacks for Federated Learning Based on Multi-Index Cascading"],"prefix":"10.1109","author":[{"given":"Jingjing","family":"Guo","sequence":"first","affiliation":[{"name":"Xidian University,School of Cyber Engineering,Xi’an,China"}]},{"given":"Yupeng","family":"Xiong","sequence":"additional","affiliation":[{"name":"Xidian University,School of Cyber Engineering,Xi’an,China"}]},{"given":"Lixiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Xidian University,School of Cyber Engineering,Xi’an,China"}]},{"given":"Kun","family":"Dong","sequence":"additional","affiliation":[{"name":"Xidian University,School of Microelectronics,Xi’an,China"}]},{"given":"Lidong","family":"Lee","sequence":"additional","affiliation":[{"name":"SourceGuard Technology Ltd,Wuhu,China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1561\/2200000083"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3256974"},{"key":"ref3","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Artificial Intelligence and Statistics","author":"McMahan","year":"2017"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3363240"},{"issue":"1","key":"ref5","first-page":"102","article-title":"Federated learning for intelligent transportation systems: A survey","volume":"24","author":"Chen","year":"2023","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/iThings-GreenCom-CPSCom-SmartData-Cybermatics62450.2024.00029"},{"issue":"09","key":"ref7","first-page":"1781","article-title":"A Survey on Attacks and Defenses in Federated Learning Systems","volume":"46","author":"Gao","year":"2023","journal-title":"Chinese Journal of Computers"},{"key":"ref8","first-page":"12613","article-title":"Fl-wbc: Enhancing robustness against model poisoning attacks in federated learning from a client perspective","volume":"34","author":"Sun","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref9","first-page":"43158","article-title":"LeadFL: Client self-defense against model poisoning in federated learning","volume-title":"International Conference on Machine Learning, PMLR","author":"Zhu"},{"key":"ref10","first-page":"1721","article-title":"Every vote counts: Ranking-Based training of federated learning to resist poisoning attacks","volume-title":"32nd USENIX Security Symposium (USENIX Security 23)","author":"Mozaffari"},{"key":"ref11","first-page":"7587","article-title":"Sparsefed: Mitigating model poisoning attacks in federated learning with sparsification","volume-title":"International Conference on Artificial Intelligence and Statistics, PMLR","author":"Panda"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24434"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3352415"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s00530-022-00965-z"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103366"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/670"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26271"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539231"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3169918"},{"key":"ref20","first-page":"62006","article-title":"Fed-FA: theoretically modeling client data divergence for federated language backdoor defense","volume":"36","author":"Zhang","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i7.26083"},{"key":"ref22","first-page":"66364","article-title":"Iba: Towards irreversible backdoor attacks in federated learning","volume":"36","author":"Nguyen","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref23","first-page":"6712","article-title":"Chameleon: Adapting to peer images for planting durable backdoors in federated learning","volume-title":"International Conference on Machine Learning, PMLR","author":"Dai"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.6"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3153135"},{"key":"ref26","first-page":"2938","article-title":"How to backdoor federated learning","volume-title":"International Conference on Artificial Intelligence and Statistics, PMLR","author":"Bagdasaryan"},{"key":"ref27","first-page":"16070","article-title":"Attack of the tails: Yes, you really can backdoor federated learning","volume":"33","author":"Wang","year":"2020","journal-title":"Advances In Neural Information Processing Systems"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.47611\/jsrhs.v12i1.3644"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.09.011"}],"event":{"name":"2025 25th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","start":{"date-parts":[[2025,7,16]]},"location":"Hangzhou, China","end":{"date-parts":[[2025,7,20]]}},"container-title":["2025 25th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11216429\/11216154\/11216436.pdf?arnumber=11216436","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T18:42:32Z","timestamp":1762195352000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11216436\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,16]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/qrs-c65679.2025.00072","relation":{},"subject":[],"published":{"date-parts":[[2025,7,16]]}}}