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SPPEAR: security & privacy-preserving architecture for participatory-sensing applications

Published: 23 July 2014 Publication History

Abstract

Recent advances in sensing, computing, and networking have paved the way for the emerging paradigm of participatory sensing (PS). The openness of such systems and the richness of user data they entail raise significant concerns for their security, privacy and resilience. Prior works addressed different aspects of the problem. But in order to reap the benefits of this new sensing paradigm, we need a comprehensive solution. That is, a secure and accountable PS system that preserves user privacy, and enables the provision of incentives to the participants. At the same time, we are after a PS system that is resilient to abusive users and guarantees privacy protection even against multiple misbehaving PS entities (servers). We address these seemingly contradicting requirements with our SPPEAR architecture. Our full blown implementation and experimental evaluation demonstrate that SPPEAR is efficient, practical, and scalable. Last but not least, we formally assess the achieved security and privacy properties. Overall, our system is a comprehensive solution that significantly extends the state-of-the-art and can catalyze the deployment of PS applications.

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      cover image ACM Conferences
      WiSec '14: Proceedings of the 2014 ACM conference on Security and privacy in wireless & mobile networks
      July 2014
      246 pages
      ISBN:9781450329729
      DOI:10.1145/2627393
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 23 July 2014

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      Author Tags

      1. anonymity
      2. participatory sensing
      3. privacy
      4. security

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      Overall Acceptance Rate 98 of 338 submissions, 29%

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      • (2024)Security and Privacy for Mobile Crowdsensing: Improving User Relevance and PrivacyComputer Security. ESORICS 2023 International Workshops10.1007/978-3-031-54204-6_28(474-493)Online publication date: 1-Mar-2024
      • (2023)A Strongly Unlinkable Group Signature Scheme with Matching-Based Verifier-Local Revocation for Privacy-Enhancing CrowdsensingIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences10.1587/transfun.2022EAP1152E106.A:12(1531-1543)Online publication date: 1-Dec-2023
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