{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T21:50:48Z","timestamp":1774475448734,"version":"3.50.1"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872416"],"award-info":[{"award-number":["61872416"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61671216"],"award-info":[{"award-number":["61671216"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871436"],"award-info":[{"award-number":["61871436"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51479159"],"award-info":[{"award-number":["51479159"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51879210"],"award-info":[{"award-number":["51879210"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51879210"],"award-info":[{"award-number":["51879210"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702204"],"award-info":[{"award-number":["61702204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872415"],"award-info":[{"award-number":["61872415"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2019kfyXJJS017"],"award-info":[{"award-number":["2019kfyXJJS017"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Suzhou\/Jiangsu Province","award":["BK20160385"],"award-info":[{"award-number":["BK20160385"]}]},{"name":"Transportation Internet of Things","award":["2018IOT004"],"award-info":[{"award-number":["2018IOT004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Sustain. Comput."],"published-print":{"date-parts":[[2020,7,1]]},"DOI":"10.1109\/tsusc.2019.2930526","type":"journal-article","created":{"date-parts":[[2019,7,23]],"date-time":"2019-07-23T20:09:50Z","timestamp":1563912590000},"page":"365-376","source":"Crossref","is-referenced-by-count":28,"title":["MIASec: Enabling Data Indistinguishability Against Membership Inference Attacks in MLaaS"],"prefix":"10.1109","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1963-4954","authenticated-orcid":false,"given":"Chen","family":"Wang","sequence":"first","affiliation":[]},{"given":"Gaoyang","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4154-8529","authenticated-orcid":false,"given":"Haojun","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Weijie","family":"Feng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9910-4237","authenticated-orcid":false,"given":"Kai","family":"Peng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2766-0845","authenticated-orcid":false,"given":"Lizhe","family":"Wang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.21"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2015.23241"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.12"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2806483"},{"key":"ref36","article-title":"Chiron: Privacy-preserving machine learning as a service","author":"hunt","year":"2018","journal-title":"CoRR"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2017.2711039"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134077"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1000167"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978355"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23183"},{"key":"ref13","article-title":"Towards measuring membership privacy","author":"long","year":"2017","journal-title":"CoRR"},{"key":"ref14","article-title":"The unintended consequences of overfitting: Training data inference attacks","author":"yeom","year":"2017","journal-title":"CoRR"},{"key":"ref15","article-title":"Understanding membership inferences on well-generalized learning models","author":"long","year":"2018","journal-title":"CoRR"},{"key":"ref16","article-title":"Towards demystifying membership inference attacks","author":"truex","year":"2018","journal-title":"CoRR"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00065"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2019.2916086"},{"key":"ref19","first-page":"17","article-title":"Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing","author":"fredrikson","year":"2014","journal-title":"Proc Usenix Security Symp"},{"key":"ref28","first-page":"1491","article-title":"Adversarial image perturbation for privacy protection&#x2013;a game theory perspective","author":"joon oh","year":"2017","journal-title":"Proc IEEE Int Conf Comput Vis"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref27","first-page":"513","article-title":"Attriguard: A practical defense against attribute inference attacks via adversarial machine learning","author":"jia","year":"2018","journal-title":"Proc Usenix Security Symp"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2017.2771424"},{"key":"ref6","first-page":"265","article-title":"Calibrating noise to sensitivity in private data analysis","author":"dwork","year":"2006","journal-title":"Proc Theory Cryptography Conf"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186095"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2019.23119"},{"key":"ref8","article-title":"Understanding deep learning requires rethinking generalization","author":"zhang","year":"2016","journal-title":"CoRR"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS.2007.66"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1600114"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2009.09.011"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1201\/9781315155678"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813677"},{"key":"ref22","article-title":"PRADA: Protecting against DNN model stealing attacks","author":"juuti","year":"2018","journal-title":"CoRR"},{"key":"ref21","first-page":"601","article-title":"Stealing machine learning models via prediction APIs","author":"tram\u00e8r","year":"2016","journal-title":"Proc Usenix Security Symp"},{"key":"ref24","first-page":"599","article-title":"Scalable optimization of randomized operational decisions in adversarial classification settings","author":"li","year":"2015","journal-title":"Proc Int Conf Artif Intell Statist"},{"key":"ref23","first-page":"485","article-title":"Optimal randomized classification in adversarial settings","author":"vorobeychik","year":"2014","journal-title":"Proc Int Conf Auton Agents and Multi Agent Syst"},{"key":"ref26","first-page":"1","article-title":"Ensemble adversarial training: Attacks and defenses","author":"kurakin","year":"2018","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"}],"container-title":["IEEE Transactions on Sustainable Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274860\/9188049\/08770147.pdf?arnumber=8770147","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T12:34:49Z","timestamp":1651062889000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8770147\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,1]]},"references-count":37,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tsusc.2019.2930526","relation":{},"ISSN":["2377-3782","2377-3790"],"issn-type":[{"value":"2377-3782","type":"electronic"},{"value":"2377-3790","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,1]]}}}