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Dynamic Spectrum Access (DSA) is a promising solution to alleviate spectrum crowding. However, geolocation database-driven spectrum access system (SAS) presents privacy risks, as sensitive Incumbent User (IU) operation parameters are required to be stored by SAS in order to perform spectrum assignments properly. These sensitive operation parameters may potentially be compromised if SAS is the target of a cyber attack or SU inference attack. In this paper, we propose a novel privacy-preserving SAS-based DSA framework, Suspicion Zone SAS (SZ-SAS). This is the first framework which protects against both the scenario of inference attacks in an area with sparsely distributed IUs and the scenario of untrusted or compromised SAS. Evaluation results show SZ-SAS is capable of utilizing compatible obfuscation schemes to prevent the SU inference attack, while operating using only homomorphically encrypted IU operation parameters.
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Comparison of Incumbent User Privacy Preserving Technologies in Database Driven Dynamic Spectrum Access Systems
Database driven dynamic spectrum sharing is one of the most promising dynamic spectrum access (DSA) solution to address the spectrum scarcity issue. In such a database driven DSA system, the centralized spectrum management infrastructure, called spectrum access system (SAS), makes its spectrum allocation decisions to secondary users (SUs) according to sensitive operational data of incumbent users (IUs). Since both SAS and SUs are not necessarily fully trusted, privacy protection against untrusted SAS and SUs become critical for IUs that have high operational privacy requirements. To address this problem, many IU privacy preserving solutions emerge recently. However, there is a lack of understanding and comparison of capability in protecting IU operational privacy under these existing approaches. In this paper, thus, we fill in the void by providing a comparative study that investigates existing solutions and explores several existing metrics to evaluate the strength of privacy protection. Moreover, we propose two general metrics to evaluate privacy preserving level and evaluate existing works with them.
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- Award ID(s):
- 1547366
- PAR ID:
- 10112731
- Date Published:
- Journal Name:
- CROWNCOM 2018: Cognitive Radio Oriented Wireless Networks
- Page Range / eLocation ID:
- 55-65
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1007/978-3-030-05490-8_6
