{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T20:23:07Z","timestamp":1760300587489,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030750749"},{"type":"electronic","value":"9783030750756"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-75075-6_28","type":"book-chapter","created":{"date-parts":[[2021,4,26]],"date-time":"2021-04-26T07:06:40Z","timestamp":1619420800000},"page":"345-357","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["PPCSA: Partial Participation-Based Compressed and Secure Aggregation in\u00a0Federated Learning"],"prefix":"10.1007","author":[{"given":"Ahmed","family":"Moustafa","sequence":"first","affiliation":[]},{"given":"Muhammad","family":"Asad","sequence":"additional","affiliation":[]},{"given":"Saima","family":"Shaukat","sequence":"additional","affiliation":[]},{"given":"Alexander","family":"Norta","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,27]]},"reference":[{"issue":"1","key":"28_CR1","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1109\/MCOM.001.1900103","volume":"58","author":"G Zhu","year":"2020","unstructured":"Zhu, G., Liu, D., Du, Y., You, C., Zhang, J., Huang, K.: Toward an intelligent edge: wireless communication meets machine learning. IEEE Commun. Mag. 58(1), 19 (2020)","journal-title":"IEEE Commun. Mag."},{"issue":"3","key":"28_CR2","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1145\/3380908.3380916","volume":"47","author":"L Su","year":"2020","unstructured":"Su, L.: Defending distributed systems against adversarial attacks: consensus, consensus based learning, and statistical learning. ACM SIGMETRICS Perform. Eval. Rev. 47(3), 24 (2020)","journal-title":"ACM SIGMETRICS Perform. Eval. Rev."},{"issue":"2","key":"28_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3298981","volume":"10","author":"Q Yang","year":"2019","unstructured":"Yang, Q., Liu, Y., Chen, T., Tong, Y.: Federated machine learning: concept and applications. ACM Trans. Intell. Syst. Technol. (TIST) 10(2), 1 (2019)","journal-title":"ACM Trans. Intell. Syst. Technol. (TIST)"},{"key":"28_CR4","unstructured":"Hu, S., Li, Y., Liu, X., Li, Q., Wu, Z., He, B.: arXiv preprint arXiv:2006.07856 (2020)"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Xu, J., Glicksberg, B.S., Su, C., Walker, P., Bian, J., Wang, F.: Federated learning for healthcare informatics. J. Healthc. Inform. Res. 1\u201319 (2020)","DOI":"10.1007\/s41666-020-00082-4"},{"key":"28_CR6","unstructured":"Samarakoon, S., Bennis, M., Saad, W., Debbah, M.: Distributed federated learning for ultra-reliable low-latency vehicular communications. IEEE Trans. Commun. 68(2), 1146\u20131159 (2019)"},{"issue":"24","key":"28_CR7","doi-asserted-by":"publisher","first-page":"7182","DOI":"10.3390\/s20247182","volume":"20","author":"M Asad","year":"2020","unstructured":"Asad, M., Moustafa, A., Yu, C.: A critical evaluation of privacy and security threats in federated learning. Sensors 20(24), 7182 (2020)","journal-title":"Sensors"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"Ketkar, N.: In: Deep Learning with Python, pp. 113\u2013132. Springer (2017)","DOI":"10.1007\/978-1-4842-2766-4_8"},{"key":"28_CR9","unstructured":"Erlingsson, \u00da., Pihur, V., Korolova, A.: In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 1054\u20131067 (2014)"},{"key":"28_CR10","unstructured":"Hanzely, F., Richt\u00e1rik, P.: arXiv preprint arXiv:2002.05516 (2020)"},{"key":"28_CR11","unstructured":"Asad, M., Moustafa, A., Ito, T., Aslam, M.: arXiv preprint arXiv:2004.02738 (2020)"},{"issue":"6","key":"28_CR12","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1109\/MNET.011.2000286","volume":"34","author":"SA Rahman","year":"2020","unstructured":"Rahman, S.A., Tout, H., Talhi, C., Mourad, A.: Internet of things intrusion detection: centralized, on-device, or federated learning? IEEE Netw. 34(6), 310 (2020)","journal-title":"IEEE Netw."},{"key":"28_CR13","unstructured":"Kairouz, P., Bonawitz, K., Ramage, D.: arXiv preprint arXiv:1602.07387 (2016)"},{"key":"28_CR14","unstructured":"McMahan, H.B., Moore, E., Ramage, D., Hampson, S., y Arcas, B.A.: arXiv preprint arXiv:1602.05629 (2016)"},{"issue":"5","key":"28_CR15","first-page":"1333","volume":"13","author":"Y Aono","year":"2017","unstructured":"Aono, Y., Hayashi, T., Wang, L., Moriai, S., et al.: Privacy-preserving deep learning via additively homomorphic encryption. IEEE Trans. Inf. Forensics Secur. 13(5), 1333 (2017)","journal-title":"IEEE Trans. Inf. Forensics Secur."}],"container-title":["Lecture Notes in Networks and Systems","Advanced Information Networking and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-75075-6_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,26]],"date-time":"2021-04-26T07:09:43Z","timestamp":1619420983000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-75075-6_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030750749","9783030750756"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-75075-6_28","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"27 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto, ON","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 May 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 May 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"35","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aina2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}