Location Privacy Preservation For Optimal Sensing In Cognitive Radio Networks
Download Location Privacy Preservation For Optimal Sensing In Cognitive Radio Networks PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Location Privacy Preservation For Optimal Sensing In Cognitive Radio Networks book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Location Privacy Preservation in Cognitive Radio Networks
This brief focuses on the current research on location privacy preservation in cognitive radio networks (CRNs). Along with a review of the existing works, this book includes fundamental privacy models, possible frameworks, useful performance, and future research directions. It explores privacy preservation techniques, collaborative spectrum sensing, database-driven CRNS, and modeling potential privacy threats. Conflicts between database owners and unlicensed users can compromise location privacy, and CRNs are a means to mitigate the spectrum scarcity issue due to the increasing demand for wireless channel resources. By examining the current and potential privacy threats, the authors equip readers to understand this developing issue. The brief is designed for researchers and professionals working with computer communication networks and cognitive radio networks. Graduate students interested in networks and communication engineering will also find the brief helpful.
Location Privacy Preservation for Optimal Sensing in Cognitive Radio Networks
Cognitive Radio Networks (CRNs) enable opportunistic access to the licensed channel resources by allowing unlicensed users to exploit vacant channel opportunities. One effective technique through which unlicensed users, often referred to as Secondary Users (SUs), acquire whether a channel is vacant is cooperative spectrum sensing. Despite its effectiveness in enabling CRN access, cooperative sensing suffers from location privacy threats, merely because the sensing reports that need to be exchanged among the SUs to perform the sensing task are highly correlated to the SUs' locations. In this thesis, we propose three private sensing protocols. The first scheme, Location Privacy for Optimal Sensing (LPOS) preserves the location privacy of SUs while achieving optimal sensing performance through voting-based sensing. In addition, LPOS is the only alternative among existing CRN location privacy preserving schemes (to the best of our knowledge) that ensures high privacy, achieves fault tolerance, and is robust against the highly dynamic and wireless nature of CRNs. We provide also a second variant of LPOS, that we call REP-LPOS which incorporates a reputation mechanism and uses Elliptic Curve El Gamal with Pollard lambda method to boost the decryption. The third scheme is called Public Register Private Sensing (PRPS) which is the most efficient scheme but offers lower privacy than LPOS and REP-LPOS.
Computer Security – ESORICS 2019
The two volume set, LNCS 11735 and 11736, constitutes the proceedings of the 24th European Symposium on Research in Computer Security, ESORIC 2019, held in Luxembourg, in September 2019. The total of 67 full papers included in these proceedings was carefully reviewed and selected from 344 submissions. The papers were organized in topical sections named as follows: Part I: machine learning; information leakage; signatures and re-encryption; side channels; formal modelling and verification; attacks; secure protocols; useful tools; blockchain and smart contracts. Part II: software security; cryptographic protocols; security models; searchable encryption; privacy; key exchange protocols; and web security.