ABSTRACT
Collaborative sensing has become increasingly popular in cognitive radio networks to enable unlicensed secondary users to coexist with the licensed primary users and share spectrum without interference. Despite its promise in performance enhancement, collaborative sensing is still facing a lot of security challenges. The problem of revealing secondary users' location information through sensing reports has been reported recently. Unlike any existing work, in this paper we not only address the location privacy issues in the collaborative sensing process against semi-honest adversaries, but also take the malicious adversaries into consideration. We propose efficient schemes to protect secondary users' report from being revealed in the report aggregation process at the fusion center. We rigorously prove that our privacy-preserving collaborative sensing schemes are secure against the fusion center and the secondary users in semi-honest model. We also evaluate our scheme extensively and verify its efficiency.
- M. Abdelraheem, M. El-Nainay, and S. Midkiff. Spectrum occupancy analysis of cooperative relaying technique for cognitive radio networks. In Computing, Networking and Communications (ICNC), 2015 International Conference on, pages 237--241, Feb 2015.Google ScholarCross Ref
- I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty. Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Comput. Netw., 50(13):2127--2159, Sept. 2006. Google ScholarDigital Library
- A. Al-Ali and K. Chowdhury. Simulating dynamic spectrum access using ns-3 for wireless networks in smart environments. In Sensing, Communication, and Networking Workshops (SECON Workshops), 2014 Eleventh Annual IEEE International Conference on, pages 28--33, June 2014.Google Scholar
- A. S. Amos Fiat. How to prove yourself: Practical solutions to identification and signature problems. Advances in Cryptology -- CRYPTO '86, Lecture Notes in Computer Science, 263:186--194, 1986. Google ScholarDigital Library
- K. Arshad. Malicious users detection in collaborative spectrum sensing using statistical tests. In Ubiquitous and Future Networks (ICUFN), 2012 Fourth International Conference on, pages 109--113, 2012.Google ScholarCross Ref
- D. Cabric, S. M. Mishra, D. Willkomm, R. Brodersen, and A. Wolisz. A cognitive radio approach for usage of virtual unlicensed spectrum. In In Proc. of 14th IST Mobile Wireless Communications Summit 2005, 2005.Google Scholar
- R. Chen and J.-M. Park. Ensuring trustworthy spectrum sensing in cognitive radio networks. In Networking Technologies for Software Defined Radio Networks, 2006. SDR '06.1st IEEE Workshop on, pages 110--119, 2006.Google ScholarCross Ref
- R. Chen, J.-M. Park, and J. Reed. Defense against primary user emulation attacks in cognitive radio networks. Selected Areas in Communications, IEEE Journal on, 26(1):25--37, 2008. Google ScholarDigital Library
- L. Duan, A. Min, J. Huang, and K. Shin. Attack prevention for collaborative spectrum sensing in cognitive radio networks. Selected Areas in Communications, IEEE Journal on, 30(9):1658--1665, 2012.Google Scholar
- FCC. Spectrum inventory table. http://www.fcc.gov/oet/info/database/spectrum/. website.Google Scholar
- Z. Gao, H. Zhu, S. Li, S. Du, and X. Li. Security and privacy of collaborative spectrum sensing in cognitive radio networks. Wireless Communications, IEEE, 19(6):106--112, 2012.Google ScholarCross Ref
- Z. Gao, H. Zhu, Y. Liu, M. Li, and Z. Cao. Location privacy leaking from spectrum utilization information in database-driven cognitive radio network. In Proceedings of the 2012 ACM conference on Computer and communications security, CCS '12, pages 1025--1027. ACM, 2012. Google ScholarDigital Library
- Z. Gao, H. Zhu, Y. Liu, M. Li, and C. Zhenfu. Location privacy in database-driven cognitive radio networks: Attacks and countermeasures. In INFOCOM, 2013 Proceedings IEEE, pages 2751--2759, April 2013.Google ScholarCross Ref
- O. Goldreich. The Foundations of Cryptography - Volume 2, Basic Applications. Cambridge University Press, 2004. Google ScholarDigital Library
- O. Goldreich, S. Micali, and A. Wigderson. How to play any mental game. In Proceedings of the nineteenth annual ACM symposium on Theory of computing, STOC '87, pages 218--229, New York, NY, USA, 1987. ACM. Google ScholarDigital Library
- S. Li, H. Zhu, Z. Gao, X. Guan, K. Xing, and X. Shen. Location privacy preservation in collaborative spectrum sensing. In INFOCOM, 2012 Proceedings IEEE, pages 729--737, 2012.Google ScholarCross Ref
- A. Min, K. Shin, and X. Hu. Secure cooperative sensing in ieee 802.22 wrans using shadow fading correlation. Mobile Computing, IEEE Transactions on, 10(10):1434--1447, 2011. Google ScholarDigital Library
- S. Mishra, A. Sahai, and R. Brodersen. Cooperative sensing among cognitive radios. In Communications, 2006. ICC '06. IEEE International Conference on, volume 4, pages 1658--1663, 2006.Google ScholarCross Ref
- H. Rifa-Pous and J. Rifa. Spectrum sharing models in cognitive radio networks. In Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2011 International Conference on, pages 503--510, 2011. Google ScholarDigital Library
- D. Teguig, B. Scheers, and V. Le Nir. Data fusion schemes for cooperative spectrum sensing in cognitive radio networks. pages 1--7, Oct 2012.Google Scholar
- N. Tran, D. Tran, L. B. Le, Z. Han, and C. S. Hong. Load balancing and pricing for spectrum access control in cognitive radio networks. In Global Communications Conference (GLOBECOM), 2014 IEEE, pages 1035--1040, Dec 2014.Google ScholarCross Ref
- A. S. Uriel Feige, Amos Fiat. Zero-knowledge proofs of identity. Journal of Cryptology, 1:77--94, 1988. Google ScholarDigital Library
- T. Wang and Y. Yang. Location privacy protection from rss localization system using antenna pattern synthesis. In INFOCOM, 2011 Proceedings IEEE, pages 2408--2416, 2011.Google ScholarCross Ref
- W. Wang, H. Li, Y. Sun, and Z. Han. Attack-proof collaborative spectrum sensing in cognitive radio networks. In Information Sciences and Systems, 2009. CISS 2009. 43rd Annual Conference on, pages 130--134, 2009.Google ScholarCross Ref
- W. Wang, H. Li, Y. Sun, and Z. Han. Catchit: Detect malicious nodes in collaborative spectrum sensing. In Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE, pages 1--6, 2009. Google ScholarDigital Library
- X. Xing, T. Jing, H. Li, Y. Huo, X. Cheng, and T. Znati. Optimal spectrum sensing interval in cognitive radio networks. IEEE Transactions on Parallel and Distributed Systems, 25(9):2408--2417, 2014.Google ScholarCross Ref
- S. Zhong. Privacy, Integrity, and Incentive-Compatibility in Computations with Untrusted Parties. PhD thesis, Yale University, 11 2004. Google ScholarDigital Library
Index Terms
- Protecting Location Information in Collaborative Sensing of Cognitive Radio Networks
Recommendations
Spectrum sensing in cognitive radio networks: the cooperation-processing tradeoff
Cognitive Radio, Software Defined Radio And Adaptive Wireless SystemsOpportunistic unlicensed access to the (temporarily) unused frequency bands across the licensed radio spectrum is currently being investigated as a means to mitigate the spectrum scarcity. Such opportunistic access calls for the implementation of ...
Group-based management for cooperative spectrum sensing in cognitive radio networks
ICACT'10: Proceedings of the 12th international conference on Advanced communication technologyIn cognitive radio networks, secondary users can opportunistically utilize the unused spectrum holes that are originally licensed to primary users. Therefore, spectrum sensing for seeking unutilized spectrum is a key element to establish cognitive radio ...
Collaborative spectrum sensing mechanism based on user incentive in cognitive radio networks
AbstractIn cognitive radio networks (CRNs), it is important for secondary users (SUs) to efficiently reuse spectrum without interfering communication of primary users (PUs). To acquire the communication opportunities, SUs first need become ...
Comments