{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T14:57:23Z","timestamp":1768316243512,"version":"3.49.0"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030323875","type":"print"},{"value":"9783030323882","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-32388-2_46","type":"book-chapter","created":{"date-parts":[[2019,10,27]],"date-time":"2019-10-27T10:04:40Z","timestamp":1572170680000},"page":"538-550","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["An Efficient Federated Learning Scheme with Differential Privacy in Mobile Edge Computing"],"prefix":"10.1007","author":[{"given":"Jiale","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Junyu","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yanchao","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Bing","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,28]]},"reference":[{"issue":"3","key":"46_CR1","doi-asserted-by":"publisher","first-page":"1628","DOI":"10.1109\/COMST.2017.2682318","volume":"19","author":"P Mach","year":"2017","unstructured":"Mach, P., Becvar, Z.: Mobile edge computing: a survey on architecture and computation offloading. IEEE Commun. Surv. Tutor. 19(3), 1628\u20131656 (2017)","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"46_CR2","doi-asserted-by":"crossref","unstructured":"Hesamifard, E., Takabi, H., Ghasemi, M., Wright, R.N.: Privacy-preserving machine learning as a service. In: Proceedings of 19th Privacy Enhancing Technologies Symposium, PETS, Barcelona, Spain, July 2018, pp. 123\u2013142 (2018)","DOI":"10.1515\/popets-2018-0024"},{"issue":"5","key":"46_CR3","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.1109\/TC.2015.2470255","volume":"65","author":"Q Zhang","year":"2016","unstructured":"Zhang, Q., Yang, L.T., Chen, Z.: Privacy preserving deep computation model on cloud for big data feature learning. IEEE Trans. Comput. 65(5), 1351\u20131362 (2016)","journal-title":"IEEE Trans. Comput."},{"key":"46_CR4","doi-asserted-by":"publisher","first-page":"18209","DOI":"10.1109\/ACCESS.2018.2820162","volume":"6","author":"J Zhang","year":"2018","unstructured":"Zhang, J., Chen, B., Zhao, Y., Cheng, X., Hu, F.: Data security and privacy-preserving in edge computing paradigm: survey and open issues. IEEE Access 6, 18209\u201318237 (2018)","journal-title":"IEEE Access"},{"key":"46_CR5","unstructured":"Smith, V., Chiang, C.-K., Sanjabi, M., Talwalkar, A.S.: Federated multi-task learning. In: Proceedings of the 32nd Annual Conference on Neural Information Processing Systems, NIPS, Long Beach, CA, USA, December 2017, pp. 4427\u20134437 (2017)"},{"issue":"2","key":"46_CR6","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. 10(2), 1\u201319 (2019)","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"46_CR7","doi-asserted-by":"crossref","unstructured":"Shokri, R., Shmatikov, V.: Privacy-preserving deep learning. In: Proceedings of the 22nd ACM Conference on Computer and Communications Security, CCS, Denver, Colorado, USA, October 2008, pp. 1310\u20131321 (2015)","DOI":"10.1145\/2810103.2813687"},{"key":"46_CR8","unstructured":"McMahan, H.B., Moore, E., Ramage, D., Hampson, S., Ag\u00fcera y Arcas, B.: Communication-efficient learning of deep networks from decentralized data. In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS, Fort Lauderadale, Florida, USA, April 2017, pp. 1\u201310 (2017)"},{"key":"46_CR9","doi-asserted-by":"crossref","unstructured":"Wang, J., Zhang, J., Bao, W., Zhu, X., Cao, B., Yu, P.S.: Not just privacy: improving performance of private deep learning in mobile cloud. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD, London, United Kingdom, August 2018, pp. 2407\u20132416 (2018)","DOI":"10.1145\/3219819.3220106"},{"key":"46_CR10","doi-asserted-by":"crossref","unstructured":"Mao, Y., Yi, S., Li, Q., Feng, J., Xu, F., Zhong, S.: Learning from differentially private neural activations with edge computing. In: Proceedings of the 3rd IEEE\/ACM Symposium on Edge Computing, SEC, Seattle, WA, USA, October 2018, pp. 90\u2013102 (2018)","DOI":"10.1109\/SEC.2018.00014"},{"issue":"1","key":"46_CR11","first-page":"1","volume":"1","author":"SA Osia","year":"2018","unstructured":"Osia, S.A., et al.: A hybrid deep learning architecture for privacy-preserving mobile analytics. ACM Trans. Knowl. Discov. Data 1(1), 1\u201321 (2018)","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"46_CR12","doi-asserted-by":"crossref","unstructured":"Fredrikson, F., Jha, S., Ristenpart, T.: Model inversion attacks that exploit confidence information and basic countermeasures. In: Proceedings of the 22th ACM Conference on Computer and Communications Security, CCS, Denver, Colorado, USA, October 2015, pp. 1322\u20131333 (2015)","DOI":"10.1145\/2810103.2813677"},{"issue":"5","key":"46_CR13","doi-asserted-by":"publisher","first-page":"1333","DOI":"10.1109\/TIFS.2017.2787987","volume":"13","author":"LT Phong","year":"2018","unstructured":"Phong, L.T., Aono, Y., Hayashi, T., Wang, L., Moriai, S.: Privacy-preserving deep learning via additively homomorphic encryption. IEEE Trans. Inf. Forensics Secur. 13(5), 1333\u20131345 (2018)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"3","key":"46_CR14","first-page":"211","volume":"9","author":"C Dwork","year":"2014","unstructured":"Dwork, C., Roth, A.: The algorithmic foundations of differential privacy. Found. Trends Theor. Comput. Sci. 9(3), 211\u2013407 (2014)","journal-title":"Found. Trends Theor. Comput. Sci."},{"key":"46_CR15","doi-asserted-by":"crossref","unstructured":"Lane, N.D., Georgiev, P.: Can deep learning revolutionize mobile sensing? In: Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications, HotMobile, Santa Fe, New Mexico, USA, February 2015, pp. 117\u2013122 (2015)","DOI":"10.1145\/2699343.2699349"},{"key":"46_CR16","doi-asserted-by":"crossref","unstructured":"Abadi, M., et al.: Deep learning with differential privacy. In: Proceedings of the 23th ACM Conference on Computer and Communications Security, CCS, Vienna, Austria, October 2016, pp. 308\u2013318 (2016)","DOI":"10.1145\/2976749.2978318"},{"issue":"2","key":"46_CR17","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","volume":"38","author":"C Dong","year":"2016","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Image super-resolution using deep convolutional networks. IEEE Trans. Pattern Anal. Mach. Intell. 38(2), 295\u2013307 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Machine Learning and Intelligent Communications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32388-2_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,27]],"date-time":"2019-10-27T10:10:18Z","timestamp":1572171018000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-32388-2_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030323875","9783030323882"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32388-2_46","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"value":"1867-8211","type":"print"},{"value":"1867-822X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"28 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MLICOM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning and Intelligent Communications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mlicom2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/mlicom.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}