In this paper, we propose new location privacy preserving schemes for database-driven cognitive radio networks that protect secondary users’ (SUs) location privacy while allowing them to learn spectrum availability in their vicinity. Our schemes harness probabilistic set membership data structures to exploit the structured nature of spectrum databases (DBs) and SUs’ queries. This enables us to create a compact representation of DB that could be queried by SUs without having to share their location with DB, thus guaranteeing their location privacy. Our proposed schemes offer different cost-performance characteristics. Our first scheme relies on a simple yet powerful two-party protocol that achieves unconditional security with a plausible communication overhead by making DB send a compacted version of its content to SU which needs only to query this data structure to learn spectrum availability. Our second scheme achieves significantly lower communication and computation overhead for SUs, but requires an additional architectural entity which receives the compacted version of the database and fetches the spectrum availability information in lieu of SUs to alleviate the overhead on the latter. We show that our schemes are secure, and also demonstrate that they offer significant advantages over existing alternatives for various performance and or security metrics.
, on the other hand, allows a client to obtain information from a database while preventing the database from learning which data is being retrieved. Several approaches have used this approach. For instance, @cite_32 propose a -based approach, termed , that relies on the scheme of @cite_33 to defend against a newly identified attack that exploits spectrum utilization pattern to localize s. @cite_14 @cite_12 propose two other -based approaches that try to minimize the number of queries by either allowing s to share their availability information with other s @cite_14 or by exploiting trajectory information to make s retrieve information for their current and future positions in the same query @cite_12 . Despite their merit in providing location privacy to s these -based approaches incur high overhead especially in terms of computation.
@cite_12 @cite_14 @cite_32 @cite_33
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Dynamic spectrum access (DSA) is envisioned as a promising framework for addressing the spectrum shortage caused by the rapid growth of connected wireless devices. In contrast to the legacy fixed spectrum allocation policies, DSA allows license-exempt users to access the licensed spectrum bands when not in use by their respective owners. More specifically, in the database-driven DSA model, mobile users issue location-based queries to a white-space database, in order to identify idle channels in their area. To preserve location privacy, existing solutions suggest the use of private information retrieval (PIR) protocols when querying the database. Nevertheless, these methods are not communication efficient and fail to take into account user mobility. In this paper, we address these shortcomings and propose an efficient privacy-preserving protocol based on the Hilbert space filling curve. We provide optimizations for mobile users that require privacy on-the-fly and users that have full a priori knowledge of their trajectory. Through experimentation with two real life datasets, we show that, compared to the current state-of-the-art protocol, our methods reduce the query response time at the mobile clients by a large factor. In the database-driven DSA model, clients learn their geographic location through a GPS device and use this location to retrieve a list of available channels from a centralized white-space database. To mitigate the potential privacy threats associated with location-based queries, existing work has proposed the use of private information retrieval (PIR) protocols when querying the database. Nevertheless, PIR protocols are very expensive and may lead to significant costs for highly mobile clients. In this paper, we propose a novel method that allows wireless users to collaborate in a peer-to-peer (P2P) manner, in order to share their cached channel availability information that is obtained from previous queries. Our experimental results with a real-life dataset show that our methods reduce the number of PIR queries by 50 to 60 , while incurring low computational and communication costs. Cognitive Radio Network (CRN) is regarded as a promising way to address the increasing demand for wireless channel resources. It solves the channel resource shortage problem by allowing a Secondary User (SU) to access the channel of a Primary User (PU) when the channel is not occupied by the PU. The latest FCC's rule in May 2012 enforces database-driven CRNs, in which an SU queries a database to obtain spectrum availability information by submitting a location based query. However, one concern about database-driven CRNs is that the queries sent by SUs will inevitably leak the location information. In this study, we identify a new kind of attack against location privacy of database-drive CRNs. Instead of directly learning the SUs' locations from their queries, our discovered attacks can infer an SU's location through his used channels. We propose Spectrum Utilization based Location Inferring Algorithm that enables the attacker to geo-locate an SU. To thwart location privacy leaking from query process, we propose a novel Private Spectrum Availability Information Retrieval scheme that utilizes a blind factor to hide the location of the SU. To defend against the discovered attack, we propose a novel prediction based Private Channel Utilization protocol that reduces the possibilities of location privacy leaking by choosing the most stable channels. We implement our discovered attack and proposed scheme on the data extracted from Google Earth Coverage Maps released by FCC. Experiment results show that the proposed protocols can significantly improve the location privacy. A Private Information Retrieval (PIR) protocol allows a user to obtain information from a database in a manner that prevents the database from knowing which data was retrieved. Although substantial progress has been made in the discovery of computationally PIR (cPIR) protocols with reduced communication complexity, there has been relatively little work in reducing the computational complexity of cPIR protocols. In particular, Sion and Carbunar argue that existing cPIR protocols are slower than the trivial PIR protocol (in overall performance). In this paper, we present a new family of cPIR protocols with a variety of security and performance properties. Our protocols enable much lower CPU overhead for the database server. When the database is viewed as a bit sequence, only addition operations are performed by the database server. The security of the general version of our protocol depends on either a Hidden Modular Group Order (HMGO) assumption, (a new assumption), or sender anonymity, and we present two specialized protocols, each of which depends on one of the two assumptions, respectively. For our trapdoor group protocol, we assume (the HMGO assumption) that given only the elements be1, ..., bet in the group Zm, where ei < m t and t is small, it is hard to compute the group order m. One version of our cPIR protocol depends only on sender anonymity, which to our knowledge, is the first cPIR protocol to depend only on an anonymity assumption. Our prototype implementation shows that our performance compares favorably with existing cPIR protocols.