{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T06:29:43Z","timestamp":1750746583681,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031192074"},{"type":"electronic","value":"9783031192081"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-19208-1_41","type":"book-chapter","created":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T00:03:45Z","timestamp":1668643425000},"page":"500-512","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Secure Aggregation Scheme for\u00a0Model Update in\u00a0Federated Learning"],"prefix":"10.1007","author":[{"given":"Baolin","family":"Wang","sequence":"first","affiliation":[]},{"given":"Chunqiang","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Zewei","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,17]]},"reference":[{"key":"41_CR1","unstructured":"Mcmahan, H.B., Moore, E., Ramage, D., Arcas, B.A.Y.: Communication-efficient learning of deep networks from decentralized data. CoRR, vol. abs\/1602.05629 (2016). [Online]. Available: http:\/\/arxiv.org\/abs\/1602.05629"},{"issue":"2","key":"41_CR2","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.1109\/TII.2021.3073925","volume":"18","author":"Z Xiong","year":"2022","unstructured":"Xiong, Z., Cai, Z., Takabi, D., Li, W.: Privacy threat and defense for federated learning with non-i.i.d. data in AIoT. IEEE Trans. Ind. Inform. 18(2), 1310\u20131321 (2022)","journal-title":"IEEE Trans. Ind. Inform."},{"key":"41_CR3","doi-asserted-by":"crossref","unstructured":"Qin, Y., Kondo, M.: Mlmg: multi-local and multi-global model aggregation for federated learning. In: 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), pp. 565\u2013571 (2021)","DOI":"10.1109\/PerComWorkshops51409.2021.9431011"},{"key":"41_CR4","unstructured":"Peter Kairouz, H., McMahan, B., Avent, B., Bellet, A.: Advances and open problems in federated learning (2021)"},{"key":"41_CR5","doi-asserted-by":"crossref","unstructured":"Li, J., Cheng, S., Li, Y., Cai, Z.: Approximate holistic aggregation in wireless sensor networks. In: 2015 IEEE 35th International Conference on Distributed Computing Systems, pp. 740\u2013741 (2015)","DOI":"10.1109\/ICDCS.2015.86"},{"key":"41_CR6","doi-asserted-by":"crossref","unstructured":"Nasr, M., Shokri, R., Houmansadr, A.: Comprehensive privacy analysis of deep learning: passive and active white-box inference attacks against centralized and federated learning. In: IEEE Symposium on Security and Privacy (SP) (2019)","DOI":"10.1109\/SP.2019.00065"},{"issue":"5","key":"41_CR7","doi-asserted-by":"publisher","first-page":"3088","DOI":"10.1109\/JIOT.2020.3007662","volume":"8","author":"J Pang","year":"2021","unstructured":"Pang, J., Huang, Y., Xie, Z., Han, Q., Cai, Z.: Realizing the heterogeneity: a self-organized federated learning framework for IoT. IEEE Internet Things J. 8(5), 3088\u20133098 (2021)","journal-title":"IEEE Internet Things J."},{"key":"41_CR8","doi-asserted-by":"crossref","unstructured":"Ganju, K., Wang, Q., Yang, w., Gunter, C.A., Borisov, N.: Property inference attacks on fully connected neural networks using permutation invariant representations. In: ACM SIGSAC Conference, pp. 619\u2013633 (2018)","DOI":"10.1145\/3243734.3243834"},{"issue":"6","key":"41_CR9","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. 54(6), 1\u201338 (2021)","journal-title":"ACM Comput. Surv."},{"key":"41_CR10","doi-asserted-by":"crossref","unstructured":"Short, A.R., Leligou, H.C., Papoutsidakis, M., Theocharis, E.: Using blockchain technologies to improve security in federated learning systems. In: 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC), pp. 1183\u20131188 (2020)","DOI":"10.1109\/COMPSAC48688.2020.00-96"},{"key":"41_CR11","doi-asserted-by":"crossref","unstructured":"Deng, Y., Han, T., Zhang, N.: Flex: trading edge computing resources for federated learning via blockchain. In: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 1\u20132 (2021)","DOI":"10.1109\/INFOCOMWKSHPS51825.2021.9484628"},{"key":"41_CR12","doi-asserted-by":"crossref","unstructured":"Xu, Y., et al.: BESIFL: blockchain empowered secure and incentive federated learning paradigm in IoT. IEEE Internet Things J. (2021)","DOI":"10.1109\/JIOT.2021.3138693"},{"issue":"1","key":"41_CR13","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/MNET.011.2000339","volume":"36","author":"L Feng","year":"2022","unstructured":"Feng, L., Yang, Z., Guo, S., Qiu, X., Li, W., Yu, P.: Two-layered blockchain architecture for federated learning over the mobile edge network. IEEE Network 36(1), 45\u201351 (2022)","journal-title":"IEEE Network"},{"issue":"9","key":"41_CR14","doi-asserted-by":"publisher","first-page":"8077","DOI":"10.1109\/JIOT.2020.2997389","volume":"7","author":"P Yuwen","year":"2020","unstructured":"Yuwen, P., Chunqiang, H., Deng, S., Alrawais, A.: R$${^2}$$peds: a recoverable and revocable privacy-preserving edge data sharing scheme. IEEE Internet Things J. 7(9), 8077\u20138089 (2020)","journal-title":"IEEE Internet Things J."},{"key":"41_CR15","unstructured":"Bonawitz, K., Ivanov, V., Kreuter, B., Marcedone, A., Seth, K.: Practical secure aggregation for federated learning on user-held data (2016)"},{"key":"41_CR16","unstructured":"Beguier C., Tramel, E.W.: SAFER: sparse secure aggregation for federated learning. CoRR abs\/2007.14861 (2020)"},{"key":"41_CR17","unstructured":"Dowlin, N., Gilad-bachrach, R., Laine, K., Lauter, K., Wernsing, J.: CryptoNets: applying neural networks to encrypted data with high throughput and accuracy. IEEE (2016)"},{"key":"41_CR18","unstructured":"Nath S., Rastogi, V.: Private aggregation of distributed time-series data. US (2012)"},{"issue":"6","key":"41_CR19","doi-asserted-by":"publisher","first-page":"1369","DOI":"10.1109\/TPDS.2021.3049915","volume":"32","author":"T Meng","year":"2021","unstructured":"Meng, T., Zhao, Y., Wolter, K., Cheng-Zhong, X.: On consortium blockchain consistency: a queueing network model approach. IEEE Trans. Parallel Dis. Syst. 32(6), 1369\u20131382 (2021)","journal-title":"IEEE Trans. Parallel Dis. Syst."},{"issue":"11","key":"41_CR20","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1145\/359168.359176","volume":"22","author":"A Shamir","year":"1979","unstructured":"Shamir, A.: How to share a secret. Commun. ACM 22(11), 612\u2013613 (1979)","journal-title":"Commun. ACM"}],"container-title":["Lecture Notes in Computer Science","Wireless Algorithms, Systems, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-19208-1_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T00:37:31Z","timestamp":1668645451000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19208-1_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031192074","9783031192081"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19208-1_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"17 November 2022","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 Algorithms, Systems, and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dalian","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wasa2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wasa-conference.org\/WASA2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"265","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"95","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"62","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"8","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}