CRFeb 14, 2016

Secure Data Storage Structure and Privacy-Preserving Mobile Search Scheme for Public Safety Networks

arXiv:1602.04493v13 citations
Originality Incremental advance
AI Analysis

This addresses privacy and security challenges in public safety networks, but it is incremental as it builds on existing secure indexing and Bloom filter methods.

The paper tackles the problem of providing secure, privacy-preserving access to personal information for public safety agents by proposing a framework with a secure data storage structure and mobile search scheme, achieving simultaneous availability and privacy with scalable performance and minimal delay.

In a Public Safety (PS) situation, agents may require critical and personally identifiable information. Therefore, not only does context and location-aware information need to be available, but also the privacy of such information should be preserved. Existing solutions do not address such a problem in a PS environment. This paper proposes a framework in which anonymized Personal Information (PI) is accessible to authorized public safety agents under a PS circumstance. In particular, we propose a secure data storage structure along with privacy-preserving mobile search framework, suitable for Public Safety Networks (PSNs). As a result, availability and privacy of PI are achieved simultaneously. However, the design of such a framework encounters substantial challenges, including scalability, reliability of the data, computation and communication and storage efficiency, etc. We leverage Secure Indexing (SI) methods and modify Bloom Filters (BFs) to create a secure data storage structure to store encrypted meta-data. As a result, our construction enables secure and privacy-preserving multi-keyword search capability. In addition, our system scales very well, maintains availability of data, imposes minimum delay, and has affordable storage overhead. We provide extensive security analysis, simulation studies, and performance comparison with the state-of-the-art solutions to demonstrate the efficiency and effectiveness of the proposed approach. To the best of our knowledge, this work is the first to address such issues in the context of PSNs.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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