Privacy-preserving reachability query services for massive networks

This paper studies privacy-preserving reachability query services under the paradigm of data outsourcing. Specifically, graph data have been outsourced to a third-party service provider (SP), query clients submit their queries to the SP, and the SP returns the query answers to the clients. However, the SP may not always be trustworthy. Hence, this paper investigates protecting the structural information of the graph data and the query answers from the SP. Existing techniques are either insecure or not scalable. This paper proposes a privacy-preserving labeling, called ppTopo. To our knowledge, ppTopo is the first work that can produce reachability index on massive networks and is secure against known plaintext attacks (KPA). Specifically, we propose a scalable index construction algorithm by employing the idea of topological folding, recently proposed by Cheng et al. We propose a novel asymmetric scalar product encryption in modulo 3 (ASPE3). It allows us to encrypt the index labels and transforms the queries into scalar products of encrypted labels. We perform an experimental study of the proposed technique on the SNAP networks. Compared with the existing methods, our results show that our technique is capable of producing the encrypted indexes at least 5 times faster for massive networks and the client's decryption time is 2-3 times smaller for most graphs.