{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:30:12Z","timestamp":1742945412024,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031714665"},{"type":"electronic","value":"9783031714672"}],"license":[{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-71467-2_4","type":"book-chapter","created":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T08:02:43Z","timestamp":1731484963000},"page":"37-49","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Method for\u00a0Abnormal Detection and\u00a0Poisoned Data Recovery in\u00a0Clustered Federated Learning"],"prefix":"10.1007","author":[{"given":"Yingying","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junyu","family":"Ye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,14]]},"reference":[{"issue":"8","key":"4_CR1","doi-asserted-by":"publisher","first-page":"3710","DOI":"10.1109\/TNNLS.2020.3015958","volume":"32","author":"F Sattler","year":"2020","unstructured":"Sattler, F., M\u00fcller, K.R., Samek, W.: Clustered federated learning: model-agnostic distributed multitask optimization under privacy constraints. IEEE Trans. Neural Netw. Learn. Syst. 32(8), 3710\u20133722 (2020)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"1","key":"4_CR2","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1109\/JIOT.2023.3299947","volume":"11","author":"Z He","year":"2024","unstructured":"He, Z., Wang, L., Cai, Z.: Clustered federated learning with adaptive local differential privacy on heterogeneous iot data. IEEE Internet Things J. (IoTJ). 11(1), 137\u2013146 (2024)","journal-title":"IEEE Internet Things J. (IoTJ)."},{"issue":"9","key":"4_CR3","doi-asserted-by":"publisher","first-page":"6273","DOI":"10.1109\/TII.2022.3145010","volume":"18","author":"S Chen","year":"2022","unstructured":"Chen, S., Yu, D., Zou, Y., Yu, J., Cheng, X.: Decentralized wireless federated learning with differential privacy. IEEE Trans. Industr. Inf. 18(9), 6273\u20136282 (2022)","journal-title":"IEEE Trans. Industr. Inf."},{"issue":"6","key":"4_CR4","doi-asserted-by":"publisher","first-page":"5211","DOI":"10.1109\/TVT.2021.3064877","volume":"70","author":"D Yu","year":"2021","unstructured":"Yu, D., et al.: Decentralized parallel SGD with privacy preservation in vehicular networks. IEEE Trans. Veh. Technol. 70(6), 5211\u20135220 (2021)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"4","key":"4_CR5","doi-asserted-by":"publisher","first-page":"1060","DOI":"10.1109\/TC.2024.3352814","volume":"73","author":"Y Yuan","year":"2024","unstructured":"Yuan, Y., et al.: Distributed learning for large-scale models at edge with privacy protection. IEEE Trans. Comput. 73(4), 1060\u20131070 (2024)","journal-title":"IEEE Trans. Comput."},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Xiong, Z., Li, W., Cai, Z.: Federated generative model on multi-source heterogeneous data in IoT. Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), vol. 37, no. 9, pp. 10537\u201310545 (2023)","DOI":"10.1609\/aaai.v37i9.26252"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Sattler, F., M\u00fcller, K.R., Wiegand, T.: On the byzantine robustness of clustered federated learning. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8861\u20138865 (2020)","DOI":"10.1109\/ICASSP40776.2020.9054676"},{"issue":"13","key":"4_CR8","doi-asserted-by":"publisher","first-page":"11365","DOI":"10.1109\/JIOT.2021.3128646","volume":"9","author":"G Sun","year":"2021","unstructured":"Sun, G., Cong, Y., Dong, J.: Data poisoning attacks on federated machine learning. IEEE Internet Things J. 9(13), 11365\u201311375 (2021)","journal-title":"IEEE Internet Things J."},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Guo, H., Mao, Y., He, X.: Improving federated learning through abnormal client detection and incentive. CMES-Compu. Model. Eng. Sci. 139(1) (2024)","DOI":"10.32604\/cmes.2023.031466"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Linghu, Y., Xu, M., Li, X.: Weighted local outlier factor for detecting anomaly on in-vehicle network. In: 2020 16th International Conference on Mobility, Sensing and Networking, pp. 479\u2013487. IEEE (2020)","DOI":"10.1109\/MSN50589.2020.00082"},{"issue":"6","key":"4_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3459992","volume":"54","author":"Z Cai","year":"2021","unstructured":"Cai, Z., Xiong, Z., Xu, H., Wang, P., Li, W., Pan, Y.: Generative adversarial networks: a survey toward private and secure applications. ACM Comput. Surv. (CSUR). 54(6), 1\u201338 (2021)","journal-title":"ACM Comput. Surv. (CSUR)."},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Cao, D., Chang, S., Lin, Z.: Understanding distributed poisoning attack in federated learning. In: 2019 IEEE 25th International Conference on Parallel and Distributed Systems, pp. 233\u2013239 (2019)","DOI":"10.1109\/ICPADS47876.2019.00042"},{"key":"4_CR13","unstructured":"Li, S., Chen, Y., Liu, Y.: Abnormal client behavior detection in federated learning. arxiv preprint arxiv:1910.09933 (2019)"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zhu, T., Chang, W.: Model poisoning defense on federated learning: a validation based approach. In: International Conference on Network and System Security, pp. 207\u2013223 (2020)","DOI":"10.1007\/978-3-030-65745-1_12"},{"issue":"35","key":"4_CR15","doi-asserted-by":"publisher","first-page":"25969","DOI":"10.1007\/s11042-020-09254-1","volume":"79","author":"J Shen","year":"2020","unstructured":"Shen, J., Lee, C., Hsu, F., Agrawal, S.: A self-embedding fragile image authentication based on singular value decomposition. Multimedia Tools Appl. 79(35), 25969\u201325988 (2020)","journal-title":"Multimedia Tools Appl."},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"Huang, L., Kuang, D., Li, C. L., Zhuang, Y. J., Duan, S. H., Zhou, X.: A self-embedding secure fragile watermarking scheme with high quality recovery. J. Vis. Commun. Image Represent. 83, 103437 (2022)","DOI":"10.1016\/j.jvcir.2022.103437"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Rakhmawati, L., Wirawan, W., Suwadi, S.: A recent survey of self-embedding fragile watermarking scheme for image authentication with recovery capability. EURASIP J. Image Video Process. 1\u201322 (2019)","DOI":"10.1186\/s13640-019-0462-3"}],"container-title":["Lecture Notes in Computer Science","Wireless Artificial Intelligent Computing Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-71467-2_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T08:03:30Z","timestamp":1731485010000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-71467-2_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,14]]},"ISBN":["9783031714665","9783031714672"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-71467-2_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,14]]},"assertion":[{"value":"14 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WASA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Wireless Artificial Intelligent Computing Systems and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Qingdao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wasa2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wasa-conference.org\/WASA2024\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}