Mechanisms to Address Different Privacy Requirements for Users and Locations
Author:
Affiliation:
1. Dept. of Social Informatics, Kyoto University
2. Graduate School / Faculty of Information Science and Technology, Hokkaido University
3. Yahoo Japan Corporation
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E106.D/12/E106.D_2023EDP7050/_pdf
Reference17 articles.
1. [1] L. Yu, L. Liu, and C. Pu, “Dynamic Differential Location Privacy with Personalized Error Bounds,” Proceedings 2017 Network and Distributed System Security Symposium, San Diego, CA, Internet Society, 2017. 10.14722/ndss.2017.23241
2. [2] S. Zhang, B. Duan, Z. Chen, T. Ni, and H. Zhong, “Regionalized location obfuscation mechanism with personalized privacy levels,” Jan. 2022. arXiv:2102.00654 [cs].
3. [3] P. Pappachan, C. Qiu, A. Squicciarini, and V.S.H. Manjunath, “User Customizable and Robust Geo-Indistinguishability for Location Privacy,” Oct. 2022. arXiv:2206.08396 [cs] version: 2.
4. [5] M. Gruteser and D. Grunwald, “Anonymous usage of location-based services through spatial and temporal cloaking,” Proceedings of the 1st International Conference on Mobile Systems, Applications and Services, MobiSys '03, New York, NY, USA, pp.31-42, Association for Computing Machinery, 2003. 10.1145/1066116.1189037
5. [6] K. Chatzikokolakis, M.E. Andrés, N.E. Bordenabe, and C. Palamidessi, “Broadening the Scope of Differential Privacy Using Metrics,” Privacy Enhancing Technologies, vol.7981, pp.82-102, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013. 10.1007/978-3-642-39077-7_5
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