{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T06:12:38Z","timestamp":1784182358849,"version":"3.55.0"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T00:00:00Z","timestamp":1777852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T00:00:00Z","timestamp":1777852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2537760"],"award-info":[{"award-number":["2537760"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,4]]},"DOI":"10.1109\/host68814.2026.11604845","type":"proceedings-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T20:02:14Z","timestamp":1784145734000},"page":"220-230","source":"Crossref","is-referenced-by-count":0,"title":["GhostTrace: A Membership Inference Attack via Hardware Performance Counters as a Side-Channel"],"prefix":"10.1109","author":[{"given":"Amisha","family":"Srivastava","sequence":"first","affiliation":[{"name":"University of Texas at Dallas,Department of Electrical and Computer Engineering,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anand","family":"Menon","sequence":"additional","affiliation":[{"name":"University of Texas at Dallas,Department of Electrical and Computer Engineering,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanjay","family":"Das","sequence":"additional","affiliation":[{"name":"University of Texas at Dallas,Department of Electrical and Computer Engineering,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kanad","family":"Basu","sequence":"additional","affiliation":[{"name":"Rensselaer Polytechnic Institute,Department of Electrical, Computer and Systems Engineering,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2019.2897554"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00780"},{"key":"ref4","article-title":"Getty images v stability ai: the implications for uk copyright law and licensing","author":"Davies","year":"2024","journal-title":"Pinsent Masons"},{"key":"ref5","author":"Rosenfeld","journal-title":"Generative al and copyright law: Current trends in litigation and legislation."},{"key":"ref6","article-title":"Nyt v. openai: The times\u2019s about-face","volume-title":"Harvard Law Review","author":"Pope","year":"2024"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/FDTC.2008.19"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3523273"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2019.23119"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CSF.2018.00027"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00065"},{"key":"ref12","first-page":"1291","article-title":"Updates-leak: Data set inference and reconstruction attacks in online learning","volume-title":"29th USENIX Security Symposium (USENIX Security 20)","author":"Salem","year":"2020"},{"key":"ref13","first-page":"681","article-title":"Leaky dnn: Stealing deeplearning models with hardware performance counters","volume-title":"Proceedings of the 2018 on Asia Conference on Computer and Communications Security (ASIACCS)","author":"Wei","year":"2018"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3373376.3378460"},{"key":"ref15","first-page":"515","article-title":"Csi neural network: Using side-channels to recover your artificial neural network information","volume-title":"28th USENIX Security Symposium (USENIX Security 19)","author":"Batina","year":"2019"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3196494.3196515"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ISVLSI59464.2023.10238603"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/VLSID60093.2024.00037"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/258916.258924"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.09.014"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3579371.3589080"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243831"},{"key":"ref23","first-page":"6861","article-title":"Privacy side channels in machine learning systems","volume-title":"33rd USENIX Security Symposium (USENIX Security 24)","author":"Debenedetti","year":"2024"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3725843.3756097"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68017-6_51"},{"key":"ref26","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009","journal-title":"University of Toronto, Tech. Rep. TR-2009"},{"key":"ref27","article-title":"tiny-imagenet","volume-title":"Hugging Face Dataset, 2022, tiny ImageNet dataset (110 k images, 200 classes, 64 \u00d7 64) in Parquet format"},{"issue":"8","key":"ref28","first-page":"2182","article-title":"Medmnist classification decathlon: A lightweight automl benchmark for medical image analysis","volume":"40","author":"Yang","year":"2021","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"ref29","article-title":"Adult [dataset]","volume-title":"UCI Machine Learning Repository","author":"Becker","year":"1996"},{"key":"ref30","article-title":"pii-masking-300k","volume-title":"Hugging Face Dataset","year":"2024"},{"key":"ref31","article-title":"gretel-pii-masking-en-v1","volume-title":"Hugging Face Dataset","year":"2025"},{"key":"ref32","article-title":"Membership inference attacks from first principles","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Carlini","year":"2021"},{"key":"ref33","doi-asserted-by":"crossref","DOI":"10.14722\/ndss.2021.24293","article-title":"Practical blind membership inference attack via differential comparisons","volume-title":"arXiv preprint","author":"Hui","year":"2021"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3548606.3560684"},{"key":"ref35","volume-title":"Cascading and proxy membership inference attacks","author":"Du","year":"2025"}],"event":{"name":"2026 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)","location":"Washington, DC, USA","start":{"date-parts":[[2026,5,4]]},"end":{"date-parts":[[2026,5,7]]}},"container-title":["2026 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11604575\/11604182\/11604845.pdf?arnumber=11604845","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T05:51:19Z","timestamp":1784181079000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11604845\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,4]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/host68814.2026.11604845","relation":{},"subject":[],"published":{"date-parts":[[2026,5,4]]}}}