Abstract
Focusing on the diversified demands of location privacy in mobile social networks (MSNs), we propose a privacy-enhancing k-nearest neighbors search scheme over MSNs. First, we construct a dual-server architecture that incorporates location privacy and fine-grained access control. Under the above architecture, we design a lightweight location encryption algorithm to achieve a minimal cost to the user. We also propose a location re-encryption protocol and an encrypted location search protocol based on secure multi-party computation and homomorphic encryption mechanism, which achieve accurate and secure k-nearest friends retrieval. Moreover, to satisfy fine-grained access control requirements, we propose a dynamic friends management mechanism based on public-key broadcast encryption. It enables users to grant/revoke others’ search right without updating their friends’ keys, realizing constant-time authentication. Security analysis shows that the proposed scheme satisfies adaptive -semantic security and revocation security under a random oracle model. In terms of performance, compared with the related works with single server architecture, the proposed scheme reduces the leakage of the location information, search pattern and the user–server communication cost. Our results show that a decentralized and end-to-end encrypted k-nearest neighbors search over MSNs is not only possible in theory, but also feasible in real-world MSNs collaboration deployment with resource-constrained mobile devices and highly iterative location update demands.
Highlights
The privacy-enhancing k-nearest neighbors search scheme over mobile social networks (MSNs) can be viewed as a decentralized system of end-to-end encrypted social network databases, focusing on the diversified demands of location privacy in MSNs
Aiming at the problem of location privacy disclosure in MSNs, we propose a privacyenhancing k-nearest neighbors search scheme over MSNs
We deploy a dual-server collaborative architecture and design an encrypted location-oriented k-neighbor search protocol based on secure multi-party computation and homomorphic encryption
Summary
Researchers have proposed many privacy-preserving approaches for MSNs. Some schemes are based on private set intersection protocols [10,11] to allow two users to compute the intersection of the two private profile sets privately, but leak no useful information of both parties. Fu et al proposed a privacy-preserving common-friend matching scheme based on a bloom filter [12] It transmitted the common profiles of two users into an intersection of bloom filters, which ensures the privacy of friend lists against unknown users. Sun et al [13] proposed a privacy-preserving spatiotemporal profiles matching scheme to let each user periodically record his locations by a geographic cell index among a large set of predefined ones, which can ensure spatiotemporal privacy at the cost of possibly huge communication and computation overhead
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