{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T22:24:53Z","timestamp":1755037493545,"version":"3.28.0"},"reference-count":34,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,3,24]]},"DOI":"10.1109\/ciss50987.2021.9400316","type":"proceedings-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T23:11:36Z","timestamp":1619046696000},"page":"1-6","source":"Crossref","is-referenced-by-count":1,"title":["Using R\u00e9nyi-divergence and Arimoto-R\u00e9nyi Information to Quantify Membership Information Leakage"],"prefix":"10.1109","author":[{"given":"Farhad","family":"Farokhi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/CSF.2018.00027"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1017\/CBO9780511804441"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1109\/TIT.2019.2962804"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1109\/TIT.2014.2357799"},{"year":"2019","author":"erlingsson","journal-title":"That which we call private","key":"ref34"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1109\/TCSS.2019.2916086"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1145\/2976749.2978355"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1145\/3243734.3243855"},{"year":"2020","author":"farokhi","journal-title":"Modelling and quantifying membership information leakage in machine learning","key":"ref13"},{"year":"2020","author":"kaya","journal-title":"On the effectiveness of regularization against membership inference attacks","key":"ref14"},{"key":"ref15","first-page":"61","article-title":"Membership inference attack against differentially private deep learning model","volume":"11","author":"rahman","year":"2018","journal-title":"Transactions on Data Privacy"},{"year":"2019","author":"leino","journal-title":"Stolen memories Leveraging model memorization for calibrated white-box membership inference","key":"ref16"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/TIT.2017.2757496"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1109\/TIT.1970.1054466"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1109\/TIT.2019.2935768"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1515\/popets-2017-0045"},{"key":"ref4","article-title":"White-box vs black-box: Bayes optimal strategies for membership inference","author":"sablayrolles","year":"2019","journal-title":"Proc of the International Conference on Machine Learning (ICML)"},{"year":"2019","author":"pyrgelis","journal-title":"Under the hood of membership inference attacks on aggregate location time-series","key":"ref27"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.14722\/ndss.2019.23119"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/CSF.2018.00027"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/ICCW.2010.5503916"},{"year":"2019","author":"yaghini","journal-title":"Disparate vulnerability On the unfairness of privacy attacks against machine learning","key":"ref5"},{"year":"2019","author":"chen","journal-title":"Gan-leaks A taxonomy of membership inference attacks against gans","key":"ref8"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.2478\/popets-2019-0008"},{"year":"2018","author":"truex","journal-title":"Towards demystifying membership inference attacks","key":"ref2"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.2478\/popets-2019-0067"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1109\/SP.2017.41"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/ISIT.2018.8437307"},{"key":"ref22","article-title":"On measures of entropy and information","author":"r\u00e9nyi","year":"1961","journal-title":"Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability Volume 1 Contributions to the Theory of Statistics"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1109\/TIT.2014.2320500"},{"key":"ref24","first-page":"1","article-title":"a-mutual information","author":"verd\u00fa","year":"2015","journal-title":"Information Theory and App Workshop (ITA) 2015"},{"key":"ref23","first-page":"1975","article-title":"Information measures and capacity of order ? for discrete memoryless channels","volume":"16","author":"arimoto","year":"0","journal-title":"Proceedings of the 2nd Colloquium on Topics on Information Theory"},{"year":"2017","author":"pyrgelis","journal-title":"Knock knock who's there? membership inference on aggregate location data","key":"ref26"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.1007\/BF00537520"}],"event":{"name":"2021 55th Annual Conference on Information Sciences and Systems (CISS)","start":{"date-parts":[[2021,3,24]]},"location":"Baltimore, MD, USA","end":{"date-parts":[[2021,3,26]]}},"container-title":["2021 55th Annual Conference on Information Sciences and Systems (CISS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9400188\/9400208\/09400316.pdf?arnumber=9400316","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T18:18:09Z","timestamp":1643393889000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9400316\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,24]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/ciss50987.2021.9400316","relation":{},"subject":[],"published":{"date-parts":[[2021,3,24]]}}}