Survey on Byzantine attacks and defenses in federated learning
Federated learning as an emerging distributed machine learning, can solve the problem of data islands. However, due to the large-scale, distributed nature and strong autonomy of local clients, federated learning is extremely vulnerable to Byzantine attacks and the attacks are not easy to detect, whi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2024-12-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024208/ |
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| _version_ | 1832595441382850560 |
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| author | ZHAO Xiaojie SHI Jinqiao HUANG Mei KE Zhenhan SHEN Liyan |
| author_facet | ZHAO Xiaojie SHI Jinqiao HUANG Mei KE Zhenhan SHEN Liyan |
| author_sort | ZHAO Xiaojie |
| collection | DOAJ |
| description | Federated learning as an emerging distributed machine learning, can solve the problem of data islands. However, due to the large-scale, distributed nature and strong autonomy of local clients, federated learning is extremely vulnerable to Byzantine attacks and the attacks are not easy to detect, which seriously damages the integrity and availability of the model. First, taking Byzantine attacks as the research object, a detailed classification and analysis of the attack principles were conducted. Secondly, guided by the classic network security defense model, federated learning defense methods were classified and analyzed from the perspective of defense mechanisms. Finally, the key issues and research challenges that need to be solved in federated learning to resist Byzantine attacks were proposed, providing new references for future relevant researchers. |
| format | Article |
| id | doaj-art-03a5915475d14733855e77614763d0d2 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2024-12-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-03a5915475d14733855e77614763d0d22025-01-18T19:00:10ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2024-12-014519721580268970Survey on Byzantine attacks and defenses in federated learningZHAO XiaojieSHI JinqiaoHUANG MeiKE ZhenhanSHEN LiyanFederated learning as an emerging distributed machine learning, can solve the problem of data islands. However, due to the large-scale, distributed nature and strong autonomy of local clients, federated learning is extremely vulnerable to Byzantine attacks and the attacks are not easy to detect, which seriously damages the integrity and availability of the model. First, taking Byzantine attacks as the research object, a detailed classification and analysis of the attack principles were conducted. Secondly, guided by the classic network security defense model, federated learning defense methods were classified and analyzed from the perspective of defense mechanisms. Finally, the key issues and research challenges that need to be solved in federated learning to resist Byzantine attacks were proposed, providing new references for future relevant researchers.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024208/federated learningByzantine attackdefense methodattack and defense strategy |
| spellingShingle | ZHAO Xiaojie SHI Jinqiao HUANG Mei KE Zhenhan SHEN Liyan Survey on Byzantine attacks and defenses in federated learning Tongxin xuebao federated learning Byzantine attack defense method attack and defense strategy |
| title | Survey on Byzantine attacks and defenses in federated learning |
| title_full | Survey on Byzantine attacks and defenses in federated learning |
| title_fullStr | Survey on Byzantine attacks and defenses in federated learning |
| title_full_unstemmed | Survey on Byzantine attacks and defenses in federated learning |
| title_short | Survey on Byzantine attacks and defenses in federated learning |
| title_sort | survey on byzantine attacks and defenses in federated learning |
| topic | federated learning Byzantine attack defense method attack and defense strategy |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024208/ |
| work_keys_str_mv | AT zhaoxiaojie surveyonbyzantineattacksanddefensesinfederatedlearning AT shijinqiao surveyonbyzantineattacksanddefensesinfederatedlearning AT huangmei surveyonbyzantineattacksanddefensesinfederatedlearning AT kezhenhan surveyonbyzantineattacksanddefensesinfederatedlearning AT shenliyan surveyonbyzantineattacksanddefensesinfederatedlearning |