Location Privacy Preserving In Cognitive Radio Networks

Cognitive Radio Network (CRN) is regarded as an effective way to address thescarcity of available wireless channel resources. It solves the channel resource short-age problem by allowing a Secondary User (SU) to access the channel of a PrimaryUser (PU) when the channel is not occupied by the PU. In a typical CRN, an SU isrequired to sense the spectrum to get the spectrum availability information before heaccesses a channel. But an individual SU’s sensing report may be not accurate e-nough due to some factors, such as fading and shadowing. Therefore, CollaborativeSpectrum Sensing is introduced to reduce the inaccuracy of sensing result. But collab-orative spectrum sensing will incur some location information leakage problems. Thisthesis identifies potential threats to location privacy, and propose the location privacypreserving scheme.The latest FCC’s (Federal Communication Commission) rule in May2012en-forces Database-driven CRNs, in which an SU queries a database to obtain spectrumavailability information of a certain region by submitting a location based query. How-ever, one concern about database-driven CRNs is that the queries sent by SUs willinevitably leak the location information of the SUs. This thesis identifies a new kindof attack against location privacy of database-drive CRNs. Instead of directly learningthe SUs’ locations from their queries, the discovered attacks can infer an SU’s locationfrom the information of his used channels. This thesis proposes Spectrum Utilizationbased Location Inferring Algorithm (SULI) that enables the attacker to geo-locate anSU. To thwart location privacy leaking from query process, this thesis proposes a novelPrivate Spectrum Availability Information Retrieval scheme that utilizes a blind factorto hide the location of the SU. To defend against the discovered SULI attack, this the-sis proposes a novel prediction based Private Channel Utilization protocol that reducesthe possibilities of location privacy leaking by choosing the most stable channels. Our attacks and the protection schemes are implemented on the data extracted from GoogleEarth Coverage Maps released by FCC. The experiment results show that the proposedprotocols can significantly improve the location privacy of database-driven CRNs.