Int. J. Communications, Network and System Sciences, 2020, 13, 73-103 https://www.scirp.org/journal/ijcns ISSN Online: 1913-3723 ISSN Print: 1913-3715 DOI: 10.4236/ijcns.2020.136006 Jun. 30, 2020 73 Int. J. Communications, Network and System Sciences Multi-Dimensional Anonymization for Participatory Sensing Systems Nafeez Abrar 1 , Shaolin Zaman 1 , Anindya Iqbal 2 , Manzur Murshed 3 1 Bangladesh University of Engineering and Technology, Dhaka, Bangladesh 2 Department of CSE, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh 3 IEEE, Federation University, Melbourne, Australia Abstract Participatory sensing systems are designed to enable community people to collect, analyze, and share information for their mutual benefit in a cost-effective way. The apparently insensitive information transmitted in plaintext through the inexpensive infrastructure can be used by an eavesdropper to infer some sensitive information and threaten the privacy of the participating users. Par- ticipation of users cannot be ensured without assuring the privacy of the par- ticipants. Existing techniques add some uncertainty to the actual observation to achieve anonymity which, however, diminishes data quality/utility to an unacceptable extent. The subset-coding based anonymization technique, DGAS [LCN 16] provides the desired level of privacy. In this research, our objective is to overcome this limitation and design a scheme with broader applicability. We have developed a computationally efficient subset-coding scheme and also present a multi-dimensional anonymization technique that anonymizes multiple properties of user observation, e.g. both location and product association of an observer in the context of consumer price sharing application. To the best of our knowledge, it is the first work which sup- ports multi-dimensional anonymization in PSS. This paper also presents an in-depth analysis of adversary threats considering collusion of adversaries and different report interception patterns. Theoretical analysis, comprehen- sive simulation, and Android prototype based experiments are carried out to establish the applicability of the proposed scheme. Also, the adversary capability is simulated to prove our scheme’s effectiveness against privacy risk. Keywords Anonymization, Privacy, Location Privacy, Participatory Sensing How to cite this paper: Abrar, N., Zaman, S., Iqbal, A. and Murshed, M. (2020) Mul- ti-Dimensional Anonymization for Parti- cipatory Sensing Systems. Int. J. Commu- nications, Network and System Sciences, 13, 73-103. https://doi.org/10.4236/ijcns.2020.136006 Received: May 24, 2020 Accepted: June 27, 2020 Published: June 30, 2020 Copyright © 2020 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access