{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T03:50:55Z","timestamp":1774583455364,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":80,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,11,13]],"date-time":"2022-11-13T00:00:00Z","timestamp":1668297600000},"content-version":"vor","delay-in-days":366,"URL":"http:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH (National Institutes of Health)","doi-asserted-by":"publisher","award":["P41EB028242"],"award-info":[{"award-number":["P41EB028242"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["ACI-1640813, CNS-1823221, CNS-1705135, CNS-1822935"],"award-info":[{"award-number":["ACI-1640813, CNS-1823221, CNS-1705135, CNS-1822935"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Combat Capabilities Development Command Army Research Laboratory","award":["W911NF-13-2-0045"],"award-info":[{"award-number":["W911NF-13-2-0045"]}]},{"name":"Intelligence Advanced Research Projects Activity (IARPA)","award":["2017-17042800006"],"award-info":[{"award-number":["2017-17042800006"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,11,12]]},"DOI":"10.1145\/3460120.3484799","type":"proceedings-article","created":{"date-parts":[[2021,11,13]],"date-time":"2021-11-13T12:05:34Z","timestamp":1636805134000},"page":"2807-2823","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["WristPrint: Characterizing User Re-identification Risks from Wrist-worn Accelerometry Data"],"prefix":"10.1145","author":[{"given":"Nazir","family":"Saleheen","sequence":"first","affiliation":[{"name":"University of Memphis, Memphis, TN, USA"}]},{"given":"Md Azim","family":"Ullah","sequence":"additional","affiliation":[{"name":"University of Memphis, Memphis, TN, USA"}]},{"given":"Supriyo","family":"Chakraborty","sequence":"additional","affiliation":[{"name":"IBM T. J. Watson Research Center, NY, NY, USA"}]},{"given":"Deniz S.","family":"Ones","sequence":"additional","affiliation":[{"name":"University of Minnesota, Minneapolis , MN, USA"}]},{"given":"Mani","family":"Srivastava","sequence":"additional","affiliation":[{"name":"University of California, Los Angeles, LA, CA, USA"}]},{"given":"Santosh","family":"Kumar","sequence":"additional","affiliation":[{"name":"University of Memphis, Memphis, TN, USA"}]}],"member":"320","published-online":{"date-parts":[[2021,11,13]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2975779"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3417287"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3463494"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3314388"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2185677.2185741"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISWC.2005.17"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3272034"},{"key":"e_1_3_2_1_8_1","volume-title":"Mobile Device Identification via Sensor Fingerprinting. arXiv preprint arXiv:1408.1416","author":"Bojinov Hristo","year":"2014","unstructured":"Hristo Bojinov, Yan Michalevsky, Gabi Nakibly, and Dan Boneh. 2014. Mobile Device Identification via Sensor Fingerprinting. arXiv preprint arXiv:1408.1416 (2014)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3339815"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.145"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3339810"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP40000.2020.00034"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinbiomech.2003.10.003"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243860"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2016.23390"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1515\/popets-2018-0005"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.23919\/EUSIPCO.2017.8081600"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2014.23059"},{"key":"e_1_3_2_1_19_1","unstructured":"Dua Dheeru and Efi Karra Taniskidou. 2017. UCI Machine Learning Repository. http:\/\/archive.ics.uci.edu\/ml"},{"key":"e_1_3_2_1_20_1","volume-title":"Proceedings of the International Conference on Mobile Computing, Applications, and Services (MobiSys). Springer, 184--201","author":"Draffin Benjamin","year":"2013","unstructured":"Benjamin Draffin, Jiang Zhu, and Joy Zhang. 2013. Keysens: Passive User Authentication Through Micro-behavior Mmodeling of Soft Keyboard Interaction. In Proceedings of the International Conference on Mobile Computing, Applications, and Services (MobiSys). Springer, 184--201."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-79228-4_1"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.3390\/s17092043"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Tim Grance Erika McCallister and Karen Scarfone. 2010. Guide to Protecting the Confidentiality of Personally Identifiable Information (PII). https:\/\/nvlpubs.nist.gov\/nistpubs\/legacy\/sp\/nistspecialpublication800--122.pdf .","DOI":"10.6028\/NIST.SP.800-122"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TrustCom.2013.272"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2012.2225048"},{"key":"e_1_3_2_1_26_1","first-page":"51","article-title":"Biometric Gait Authentication Using Accelerometer Sensor","volume":"1","author":"Gafurov Davrondzhon","year":"2006","unstructured":"Davrondzhon Gafurov, Kirsi Helkala, and Torkjel S\u00f8ndrol. 2006. Biometric Gait Authentication Using Accelerometer Sensor. JCP, Vol. 1, 7 (2006), 51--59.","journal-title":"JCP"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Simson L. Garfinkel. 2015. De-identification of Personal Information. https:\/\/nvlpubs.nist.gov\/nistpubs\/ir\/2015\/nist.ir.8053.pdf .","DOI":"10.6028\/NIST.IR.8053"},{"key":"e_1_3_2_1_28_1","volume-title":"Data Anonymization and GDPR Compliance: The Case of Taxa 4\u00d735. https:\/\/gdpr.eu\/data-anonymization-taxa-4x35\/. [Online","author":"GDPR.","year":"2021","unstructured":"GDPR. 2021. Data Anonymization and GDPR Compliance: The Case of Taxa 4\u00d735. https:\/\/gdpr.eu\/data-anonymization-taxa-4x35\/. [Online; accessed 06-Sept-2021]."},{"key":"e_1_3_2_1_29_1","volume-title":"Recent Advances in Open Set Recognition: A Survey","author":"Geng Chuanxing","year":"2020","unstructured":"Chuanxing Geng, Sheng-jun Huang, and Songcan Chen. 2020. Recent Advances in Open Set Recognition: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (2020)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2019-0008"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2015.7054716"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3131672.3131694"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2016.2611489"},{"key":"e_1_3_2_1_34_1","volume-title":"Mark Stamp, and Preethi Sundaravaradhan.","author":"Huang Elliu","year":"2021","unstructured":"Elliu Huang, Fabio Di Troia, Mark Stamp, and Preethi Sundaravaradhan. 2021. A New Dataset for Smartphone Gesture-based Authentication. (2021)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"crossref","unstructured":"Ankita Jain and Vivek Kanhangad. 2016. Investigating Gender Recognition in Smartphones Using Accelerometer and Gyroscope Sensor Readings. In 2016 international conference on computational techniques in information and communication technologies (ICCTICT). IEEE 597--602.","DOI":"10.1109\/ICCTICT.2016.7514649"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2001.958106"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/83.841531"},{"key":"e_1_3_2_1_38_1","volume-title":"Proceedings of the USENIX Security Symposium (USENIX Security 19)","author":"Jayaraman Bargav","year":"2019","unstructured":"Bargav Jayaraman and David Evans. 2019. Evaluating Differentially Private Machine Learning in Practice. In Proceedings of the USENIX Security Symposium (USENIX Security 19). 1895--1912."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1002\/sec.1061"},{"key":"e_1_3_2_1_40_1","volume-title":"Emre Ertin, Deborah Estrin, Deepak Ganesan, Timothy Hnat, Syed Monowar Hossain, et al.","author":"Kumar Santosh","year":"2017","unstructured":"Santosh Kumar, Gregory Abowd, William T Abraham, Mustafa Al'Absi, Duen Horng Chau, Emre Ertin, Deborah Estrin, Deepak Ganesan, Timothy Hnat, Syed Monowar Hossain, et al. 2017. Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K). IEEE pervasive computing, Vol. 16, 2 (2017), 18--22."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS.2010.5634532"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2007.367856"},{"key":"e_1_3_2_1_43_1","volume-title":"DEEProtect: Enabling Inference-based Access Control on Mobile Sensing Applications. CoRR","author":"Liu Changchang","year":"2017","unstructured":"Changchang Liu, Supriyo Chakraborty, and Prateek Mittal. 2017. DEEProtect: Enabling Inference-based Access Control on Mobile Sensing Applications. CoRR, Vol. abs\/1702.06159 (2017)."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/1217299.1217302"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3195258.3195260"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2005.1415569"},{"key":"e_1_3_2_1_47_1","volume-title":"Multimodal Sensing of Information Workers. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1--8.","author":"Mattingly Stephen M","year":"2019","unstructured":"Stephen M Mattingly, Julie M Gregg, Pino Audia, Ayse Elvan Bayraktaroglu, Andrew T Campbell, Nitesh V Chawla, Vedant Das Swain, Munmun De Choudhury, Sidney K D'Mello, Anind K Dey, et al. 2019. The Tesserae Project: Large-scale, Longitudinal, in Situ, Multimodal Sensing of Information Workers. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1--8."},{"key":"e_1_3_2_1_48_1","volume-title":"Towards Remote Assessment and Screening of Acute Abdominal Pain Using Only A Smartphone with Native Accelerometers. Scientific reports","author":"Myers David R","year":"2017","unstructured":"David R Myers, Alexander Weiss, Margo R Rollins, and Wilbur A Lam. 2017. Towards Remote Assessment and Screening of Acute Abdominal Pain Using Only A Smartphone with Native Accelerometers. Scientific reports, Vol. 7, 1 (2017), 1--12."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.31"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243855"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/2594368.2594379"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/DSAA.2016.49"},{"key":"e_1_3_2_1_53_1","volume-title":"Handbook of face recognition","author":"Phillips P Jonathon","unstructured":"P Jonathon Phillips, Patrick Grother, and Ross Micheals. 2011. Evaluation Methods in Face Recognition. In Handbook of face recognition. Springer, 551--574."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/772862.772865"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2014.20"},{"key":"e_1_3_2_1_56_1","unstructured":"RAAMP2. 2020. Rapid Automatic & Adaptive Model for Performance Prediction (RAAMP2) Dataset."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2011.2182616"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/2750858.2806897"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971753"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/2500423.2500434"},{"key":"e_1_3_2_1_62_1","volume-title":"Membership Inference Attacks Against Machine Learning Models. In IEEE Symposium on Security and Privacy (S&P). IEEE, 3--18","author":"Shokri Reza","year":"2017","unstructured":"Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017. Membership Inference Attacks Against Machine Learning Models. In IEEE Symposium on Security and Privacy (S&P). IEEE, 3--18."},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813679"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-02937-5_11"},{"key":"e_1_3_2_1_65_1","volume-title":"Proceedings of the $$USENIX$$ Security Symposium ($$USENIX$$ Security) .","author":"Singh Akash Deep","year":"2021","unstructured":"Akash Deep Singh, Luis Garcia, Joseph Noor, and Mani Srivastava. 2021. I Always Feel Like Somebody's Sensing Me! A Framework to Detect, Identify, and Localize Clandestine Wireless Sensors. In Proceedings of the $$USENIX$$ Security Symposium ($$USENIX$$ Security) ."},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243768"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218488502001648"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/2750858.2807545"},{"key":"e_1_3_2_1_69_1","volume-title":"Lei Yu, and Wenqi Wei.","author":"Truex Stacey","year":"2018","unstructured":"Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei. 2018. Towards Demystifying Membership Inference Attacks. arXiv preprint arXiv:1807.09173 (2018)."},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/MPRV.2017.3971131"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3412382.3458776"},{"key":"e_1_3_2_1_72_1","volume-title":"WISDM Smartphone and Smartwatch Activity and Biometrics Dataset Data Set","author":"Weiss Gary M","year":"2019","unstructured":"Gary M Weiss. 2019. WISDM Smartphone and Smartwatch Activity and Biometrics Dataset. UCI Machine Learning Repository, WISDM Smartphone and Smartwatch Activity and Biometrics Dataset Data Set (2019)."},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46478-7_31"},{"key":"e_1_3_2_1_74_1","unstructured":"Lei Xu Maria Skoularidou Alfredo Cuesta-Infante and Kalyan Veeramachaneni. 2019. Modeling Tabular data using Conditional GAN. In Advances in Neural Information Processing Systems (NeurIPS) ."},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-40548-3_90"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2014.2341633"},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472194"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00072"},{"key":"e_1_3_2_1_79_1","unstructured":"Zhilu Zhang and Mert Sabuncu. 2018. Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels. In Advances in Neural Information Processing Systems (NeurIPS). 8778--8788."},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2019.2892440"}],"event":{"name":"CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security","location":"Virtual Event Republic of Korea","acronym":"CCS '21","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"]},"container-title":["Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460120.3484799","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3460120.3484799","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3460120.3484799","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T20:54:39Z","timestamp":1763499279000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460120.3484799"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,12]]},"references-count":80,"alternative-id":["10.1145\/3460120.3484799","10.1145\/3460120"],"URL":"https:\/\/doi.org\/10.1145\/3460120.3484799","relation":{},"subject":[],"published":{"date-parts":[[2021,11,12]]},"assertion":[{"value":"2021-11-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}