Abstract
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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Ateniese, G., Fu, K., Green, M., Hohenberger, S.: Improved proxy re-encryption schemes with applications to secure distributed storage. ACM Trans. Inf. Syst. Secur. 9(1), 1–30 (2006). https://doi.org/10.1145/1127345.1127346
Bahrak, B., Bhattarai, S., Ullah, A., Park, J.M.J., Reed, J., Gurney, D.: Protecting the primary users’ operational privacy in spectrum sharing. In: 2014 IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN), pp. 236–247, April 2014. https://doi.org/10.1109/DySPAN.2014.6817800
Dou, Y., et al.: Preserving incumbent users’ privacy in server-driven dynamic spectrum access systems. In: 2016 IEEE 36th International Conference on Distributed Computing Systems (ICDCS), pp. 729–730, June 2016. https://doi.org/10.1109/ICDCS.2016.40
Park, J.M., Reed, J.H., Beex, A.A., Clancy, T.C., Kumar, V., Bahrak, B.: Security and enforcement in spectrum sharing. Proc. IEEE 102(3), 270–281 (2014). https://doi.org/10.1109/JPROC.2014.2301972
Shokri, R., Theodorakopoulos, G., Le Boudec, J.Y., Hubaux, J.P.: Quantifying location privacy. In: Proceedings of the 2011 IEEE Symposium on Security and Privacy, SP 2011, pp. 247–262. IEEE Computer Society, Washington, DC (2011). https://doi.org/10.1109/SP.2011.18
Zhang, L., Fang, C., Li, Y., Zhu, H., Dong, M.: Optimal strategies for defending location inference attack in database-driven CRNs. In: 2015 IEEE International Conference on Communications (ICC), pp. 7640–7645, June 2015. https://doi.org/10.1109/ICC.2015.7249548
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zabransky, D., Li, H., Lu, C., Yang, Y. (2019). SZ-SAS: A Framework for Preserving Incumbent User Privacy in SAS-Based DSA Systems. In: Moerman, I., Marquez-Barja, J., Shahid, A., Liu, W., Giannoulis, S., Jiao, X. (eds) Cognitive Radio Oriented Wireless Networks. CROWNCOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-030-05490-8_8
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DOI: https://doi.org/10.1007/978-3-030-05490-8_8
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