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Published in: Telecommunication Systems 1/2019

29-05-2018

Defence against PUE attacks in ad hoc cognitive radio networks: a mean field game approach

Authors: Saim Bin Abdul Khaliq, Muhammad Faisal Amjad, Haider Abbas, Narmeen Shafqat, Hammad Afzal

Published in: Telecommunication Systems | Issue 1/2019

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Abstract

Cognitive Radio (CR) is an emerging and promising communication technology geared towards improving vacant licensed band utilization, intended for unlicensed users. Security of Cognitive Radio Networks (CRN) is a highly challenging domain. At present, plenty of efforts are in place for defining new paradigms, techniques and technologies to secure radio spectrum. In a distributed cognitive radio ad-hoc network, despite dynamically changing topologies, lack of central administration, bandwidth-constraints and shared wireless connections, the nodes are capable of sensing the spectrum and selecting the appropriate channels for communication. These unique characteristics unlock new paths for attackers. Standard security techniques are not an effective shield against attacks on these networks e.g. Primary User Emulation (PUE) attacks. The paper presents a novel PUE attack detection technique based on energy detection and location verification. Next, a game model and a mean field game approach are introduced for the legitimate nodes of CRN to reach strategic defence decisions in the presence of multiple attackers. Simulation of the proposed technique shows a detection accuracy of \({89\%}\) when the probability of false alarm is 0.09. This makes it 1.32 times more accurate than compared work. Furthermore, the proposed framework for defence is state considerate in making decisions.

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Literature
2.
go back to reference Zhao, Q., & Sadler, B. M. (2007). A survey of dynamic spectrum access. IEEE Signal Processing Magazine, 24(3), 7989.CrossRef Zhao, Q., & Sadler, B. M. (2007). A survey of dynamic spectrum access. IEEE Signal Processing Magazine, 24(3), 7989.CrossRef
3.
go back to reference Lien, S.-Y., Chen, K.-C., & Liang, Y.-C. (2014). Lin Y Cognitive radio resource management for future cellular networks. IEEE Wireless Communication, 21(1), 7079.CrossRef Lien, S.-Y., Chen, K.-C., & Liang, Y.-C. (2014). Lin Y Cognitive radio resource management for future cellular networks. IEEE Wireless Communication, 21(1), 7079.CrossRef
4.
go back to reference Marinho, J., Granjal, J., & Monteiro, E. (2015). A survey on security attacks and countermeasures with primary user detection in cognitive radio networks. EURASIP Journal on Information Security, 114. Marinho, J., Granjal, J., & Monteiro, E. (2015). A survey on security attacks and countermeasures with primary user detection in cognitive radio networks. EURASIP Journal on Information Security, 114.
7.
go back to reference Jana, S., Zeng, K., & Cheng, W. (2013). Trusted collaborative spectrum sensing for mobile cognitive radio networks. IEEE Transactions on Information Forensics and Security, 8(9), 1497–1507.CrossRef Jana, S., Zeng, K., & Cheng, W. (2013). Trusted collaborative spectrum sensing for mobile cognitive radio networks. IEEE Transactions on Information Forensics and Security, 8(9), 1497–1507.CrossRef
8.
go back to reference Wengui, S., & Yang, L. (2015). A jury-based trust management mechanism in distributed cognitive radio networks. China Communications IEEE, 12(7), 119–126.CrossRef Wengui, S., & Yang, L. (2015). A jury-based trust management mechanism in distributed cognitive radio networks. China Communications IEEE, 12(7), 119–126.CrossRef
9.
go back to reference Pu, D. (2012). Detecting primary user emulation attack in cognitive radio networks. In Proc. IEEE global telecommunications conf, Dec. Pu, D. (2012). Detecting primary user emulation attack in cognitive radio networks. In Proc. IEEE global telecommunications conf, Dec.
10.
go back to reference Jin, Z., Anand, S., & Subbalakshmi, K. P. (2009). Detecting primary user emulation attacks in dynamic spectrum access networks. In Proc. IEEE Intl Conf. Commun. (ICC). Jin, Z., Anand, S., & Subbalakshmi, K. P. (2009). Detecting primary user emulation attacks in dynamic spectrum access networks. In Proc. IEEE Intl Conf. Commun. (ICC).
11.
go back to reference Akhunzada, A., Ahmed, E., Gani, A., Khan, M. K., Imran, M., & Guizani, S. (2015). Securing software defined networks: Taxonomy, requirements, and open issues. IEEE Communications Magazine, 53(4), 3644.CrossRef Akhunzada, A., Ahmed, E., Gani, A., Khan, M. K., Imran, M., & Guizani, S. (2015). Securing software defined networks: Taxonomy, requirements, and open issues. IEEE Communications Magazine, 53(4), 3644.CrossRef
12.
go back to reference Kumari, S., Khan, M. K., & Atiquzzaman, M. (2015). User authentication schemes for wireless sensor networks: A review. Ad Hoc Networks, 27, 159–194.CrossRef Kumari, S., Khan, M. K., & Atiquzzaman, M. (2015). User authentication schemes for wireless sensor networks: A review. Ad Hoc Networks, 27, 159–194.CrossRef
13.
go back to reference Tai, W.-L., Chang, Y.-F., & Chen, Y.-C. (2016). A fast-handover-supported authentication protocol for vehicular ad hoc networks. Journal of Information Hiding and Multimedia Signal Processing, 7(5), 960–969. Tai, W.-L., Chang, Y.-F., & Chen, Y.-C. (2016). A fast-handover-supported authentication protocol for vehicular ad hoc networks. Journal of Information Hiding and Multimedia Signal Processing, 7(5), 960–969.
14.
go back to reference Ngo, N. M., Unoki, M., Miyauchi, R., & Suzuki, Y. (2014). Data hiding scheme for amplitude modulation radio broadcasting systems. Journal of Information Hiding and Multimedia Signal Processing, 5(3), 324–341. Ngo, N. M., Unoki, M., Miyauchi, R., & Suzuki, Y. (2014). Data hiding scheme for amplitude modulation radio broadcasting systems. Journal of Information Hiding and Multimedia Signal Processing, 5(3), 324–341.
15.
go back to reference Nadeem, A., & Howarth, M. P. (2013). A survey of MANET intrusion detection and prevention approaches for network layer attacks. IEEE Communications Surveys and Tutorials, 15, 2027–2045.CrossRef Nadeem, A., & Howarth, M. P. (2013). A survey of MANET intrusion detection and prevention approaches for network layer attacks. IEEE Communications Surveys and Tutorials, 15, 2027–2045.CrossRef
16.
go back to reference Yang, H., Luo, H., Ye, F., Lu, S., & Zhang, L. (2004). Security in mobile ad hoc networks: Challenges and solutions. IEEE Transactions on Wireless Communications, 11, 3847. Yang, H., Luo, H., Ye, F., Lu, S., & Zhang, L. (2004). Security in mobile ad hoc networks: Challenges and solutions. IEEE Transactions on Wireless Communications, 11, 3847.
17.
go back to reference Albers, P., Camp, O. Percher, J. M., Jouga, B., Me, L., & Puttini, R. Security in ad hoc networks: A general intrusion detection architecture enhancing trust based approaches. In Proceedings of the 1st international workshop on wireless information systems. Albers, P., Camp, O. Percher, J. M., Jouga, B., Me, L., & Puttini, R. Security in ad hoc networks: A general intrusion detection architecture enhancing trust based approaches. In Proceedings of the 1st international workshop on wireless information systems.
20.
go back to reference Marti, S., Giuli, T. J., Lai, K., & Baker, M. (2010). Mitigating routing misbehaviour in mobile ad hoc networks. In Proceedings of the 6th international conference on mobile computing and networking, Boston, MA, pp. 255–265. Marti, S., Giuli, T. J., Lai, K., & Baker, M. (2010). Mitigating routing misbehaviour in mobile ad hoc networks. In Proceedings of the 6th international conference on mobile computing and networking, Boston, MA, pp. 255–265.
21.
go back to reference Zhang, Y., & Lee, W. (2013). Intrusion detection in wireless ad hoc networks. In ACM MOBICOM, pp. 275–283. Zhang, Y., & Lee, W. (2013). Intrusion detection in wireless ad hoc networks. In ACM MOBICOM, pp. 275–283.
22.
go back to reference Albers, P., Camp, O., Percher, J. M., Jouga, B., Me, L., & Puttini, R. (2012). Security in ad hoc networks: A general intrusion detection architecture enhancing trust based approaches. In Proceedings of the 1st international workshop on wireless information systems (WIS-2002) (pp. 1–12). Albers, P., Camp, O., Percher, J. M., Jouga, B., Me, L., & Puttini, R. (2012). Security in ad hoc networks: A general intrusion detection architecture enhancing trust based approaches. In Proceedings of the 1st international workshop on wireless information systems (WIS-2002) (pp. 1–12).
23.
go back to reference Ferraz, L., et al. (2014). An accurate and precise malicious node exclusion mechanism for ad hoc networks. Ad Hoc Networks, Elsevier, pp. l–14 Ferraz, L., et al. (2014). An accurate and precise malicious node exclusion mechanism for ad hoc networks. Ad Hoc Networks, Elsevier, pp. l–14
24.
go back to reference Chen, R., & Park, J.-M. (2006). Ensuring trustworthy spectrum sensing in cognitive radio networks. In First IEEE workshop on networking technologies for software defined radio networks (SDR) (pp. 110–119). VA, September: Reston. Chen, R., & Park, J.-M. (2006). Ensuring trustworthy spectrum sensing in cognitive radio networks. In First IEEE workshop on networking technologies for software defined radio networks (SDR) (pp. 110–119). VA, September: Reston.
25.
go back to reference Chen, R., Park, J.-M., & Reed, J. H. (2008). Defense against primary user emulation attacks in cognitive radio networks. IEEE Journal on Selected Areas in Communications, 26(1), 25–37.CrossRef Chen, R., Park, J.-M., & Reed, J. H. (2008). Defense against primary user emulation attacks in cognitive radio networks. IEEE Journal on Selected Areas in Communications, 26(1), 25–37.CrossRef
26.
go back to reference Huang, L., Xie, L., Yu, H., Wang, W., & Yao, Y. (2010) Anti-PUE attack based on joint position verification in cognitive radio networks. In International conference on communications and mobile computing (CMC), Vol. 2, Shenzhen, China, pp. 169–173. Huang, L., Xie, L., Yu, H., Wang, W., & Yao, Y. (2010) Anti-PUE attack based on joint position verification in cognitive radio networks. In International conference on communications and mobile computing (CMC), Vol. 2, Shenzhen, China, pp. 169–173.
27.
go back to reference Zhao, C., Wang, W., Huang, L., & Yao, Y. (2009). Anti-PUE attack base on the transmitter fingerprint identification in cognitive radio. In 5th International conference on wireless communications, networking and mobile computing (WiCom 09), Beijing, China, pp. 1–5. Zhao, C., Wang, W., Huang, L., & Yao, Y. (2009). Anti-PUE attack base on the transmitter fingerprint identification in cognitive radio. In 5th International conference on wireless communications, networking and mobile computing (WiCom 09), Beijing, China, pp. 1–5.
28.
go back to reference Afolabi, O. R., Kim, K., & Ahmad, A. (2009). Secure spectrum sensing in cognitive radio networks using emitters electromagnetic signature. In Proceedings of 18th international conference on computer communications and networks (ICCCN 2009), San Francisco, CA, pp. 1–5. Afolabi, O. R., Kim, K., & Ahmad, A. (2009). Secure spectrum sensing in cognitive radio networks using emitters electromagnetic signature. In Proceedings of 18th international conference on computer communications and networks (ICCCN 2009), San Francisco, CA, pp. 1–5.
29.
go back to reference Otrok, H., et al. (2008). A game-theoretic intrusion detection model for mobile ad hoc networks. Elsevier Computer Communications, 31, 708–721.CrossRef Otrok, H., et al. (2008). A game-theoretic intrusion detection model for mobile ad hoc networks. Elsevier Computer Communications, 31, 708–721.CrossRef
30.
go back to reference Liang, X., & Xiao, Y. (2013). Game theory for network security. IEEE Communication. Surveys Tutorials, 15(1), 472486.CrossRef Liang, X., & Xiao, Y. (2013). Game theory for network security. IEEE Communication. Surveys Tutorials, 15(1), 472486.CrossRef
31.
go back to reference Meriaux, F., Varma, V., & Lasaulce, S. Mean field energy games in wireless networks. In Proc. 2012 Asilomar conf. signals, systems., computers. Meriaux, F., Varma, V., & Lasaulce, S. Mean field energy games in wireless networks. In Proc. 2012 Asilomar conf. signals, systems., computers.
32.
go back to reference Tembine, H., Vilanova, P., Assaad, M., & Debbah, M. Mean field stochastic games for SINR-based medium access control. In Proc. 2011 intl ICST conf. performance evaluation methodologies tools. Tembine, H., Vilanova, P., Assaad, M., & Debbah, M. Mean field stochastic games for SINR-based medium access control. In Proc. 2011 intl ICST conf. performance evaluation methodologies tools.
33.
go back to reference Huang, M. Y. Mean field stochastic games with discrete states and mixed players. In Proc. 2012 GameNets. Huang, M. Y. Mean field stochastic games with discrete states and mixed players. In Proc. 2012 GameNets.
34.
go back to reference Wang, Y., Yu, F., Tang, H., & Huang, M. (2014). A mean field game theoretic approach for security enhancements in mobile ad hoc networks. IEEE Transactions on Wireless Communications, 13(3), 16161627. Wang, Y., Yu, F., Tang, H., & Huang, M. (2014). A mean field game theoretic approach for security enhancements in mobile ad hoc networks. IEEE Transactions on Wireless Communications, 13(3), 16161627.
35.
go back to reference Trees, H. L. V. (2001). Detection, estimation, and modulation theory: Part I. New Jersey, USA: Wiley-Inter science.CrossRef Trees, H. L. V. (2001). Detection, estimation, and modulation theory: Part I. New Jersey, USA: Wiley-Inter science.CrossRef
36.
go back to reference Tandra, R., & Sahai, A. (2008). SNR walls for signal detection. IEEE Journal of Selected Topics in Signal Processing, 2(1), 417.CrossRef Tandra, R., & Sahai, A. (2008). SNR walls for signal detection. IEEE Journal of Selected Topics in Signal Processing, 2(1), 417.CrossRef
37.
go back to reference Le, T. N., Chin, W.-L., & Lin, Y.-H. Non-cooperative and cooperative PUEA detection using physical layer in mobile OFDM-based cognitive radio networks. In International conference on computing, networking and communications, 24 March 2016. Le, T. N., Chin, W.-L., & Lin, Y.-H. Non-cooperative and cooperative PUEA detection using physical layer in mobile OFDM-based cognitive radio networks. In International conference on computing, networking and communications, 24 March 2016.
38.
go back to reference Urkowitz, H. (1967). Energy detection of unknown deterministic signals. Proceedings of the IEEE, 55(4), 523–531.CrossRef Urkowitz, H. (1967). Energy detection of unknown deterministic signals. Proceedings of the IEEE, 55(4), 523–531.CrossRef
39.
go back to reference Ayyasamy, A., & Venkatachalapathy, K. (2015). Context aware adaptive fuzzy based QoS routing scheme for streaming services over MANETs. Wireless Networks, 21(2), 421–30.CrossRef Ayyasamy, A., & Venkatachalapathy, K. (2015). Context aware adaptive fuzzy based QoS routing scheme for streaming services over MANETs. Wireless Networks, 21(2), 421–30.CrossRef
40.
go back to reference Ahmadi, M., Shojafar, M., Khademzadeh, A., Badie, K., & Tavoli, R. (2015). A hybrid algorithm for preserving energy and delay routing in mobile ad-hoc networks. Wireless Personal Communications, 85(4), 2485–505.CrossRef Ahmadi, M., Shojafar, M., Khademzadeh, A., Badie, K., & Tavoli, R. (2015). A hybrid algorithm for preserving energy and delay routing in mobile ad-hoc networks. Wireless Personal Communications, 85(4), 2485–505.CrossRef
41.
go back to reference Cordeschi, N., Amendola, D., & Baccarelli, E. (2015). Distributed and adaptive resource management in cloud-assisted cognitive radio vehicular networks with hard reliability guarantees. Vehicular Communications, 2(1), 1–12.CrossRef Cordeschi, N., Amendola, D., & Baccarelli, E. (2015). Distributed and adaptive resource management in cloud-assisted cognitive radio vehicular networks with hard reliability guarantees. Vehicular Communications, 2(1), 1–12.CrossRef
42.
go back to reference Zhu, J., Song, Y., Jiang, D., & Song, H. (2016). Multi-armed bandit channel access scheme with cognitive radio technology in wireless sensor networks for the internet of things. IEEE Access, 4, 4609–4617.CrossRef Zhu, J., Song, Y., Jiang, D., & Song, H. (2016). Multi-armed bandit channel access scheme with cognitive radio technology in wireless sensor networks for the internet of things. IEEE Access, 4, 4609–4617.CrossRef
43.
go back to reference Pei, Y., Liang, Y.-C., Zhang, L., The, K. C., & Li, K. H. (2010). Secure communication over MISO cognitive radio channels. IEEE Transactions on Wireless Communications, 9, 1494502.CrossRef Pei, Y., Liang, Y.-C., Zhang, L., The, K. C., & Li, K. H. (2010). Secure communication over MISO cognitive radio channels. IEEE Transactions on Wireless Communications, 9, 1494502.CrossRef
44.
go back to reference Amjad, M. F., Aslam, B. & Zou, C. C. (2013). Reputation aware collaborative spectrum sensing for mobile cognitive radio networks. In MILCOM 2013 (pp. 951–956). San Diego, CA, 18-20. Amjad, M. F., Aslam, B. & Zou, C. C. (2013). Reputation aware collaborative spectrum sensing for mobile cognitive radio networks. In MILCOM 2013 (pp. 951–956). San Diego, CA, 18-20.
45.
go back to reference Mneimneh, S., & Bhunia, S. (2017). A game-theoretic and stochastic survivability mechanism against induced attacks in Cognitive Radio Networks. Pervasive and Mobile Computing Archive, 40(C), 577–592.CrossRef Mneimneh, S., & Bhunia, S. (2017). A game-theoretic and stochastic survivability mechanism against induced attacks in Cognitive Radio Networks. Pervasive and Mobile Computing Archive, 40(C), 577–592.CrossRef
46.
go back to reference Hosseini, A., Abolhassani, B., & Hosseini, A. (2017). Secure cognitive radio communication for internet-of-things: Anti-PUE attack based on graph theory. Journal of Computer and Communications, 5, 27–39.CrossRef Hosseini, A., Abolhassani, B., & Hosseini, A. (2017). Secure cognitive radio communication for internet-of-things: Anti-PUE attack based on graph theory. Journal of Computer and Communications, 5, 27–39.CrossRef
Metadata
Title
Defence against PUE attacks in ad hoc cognitive radio networks: a mean field game approach
Authors
Saim Bin Abdul Khaliq
Muhammad Faisal Amjad
Haider Abbas
Narmeen Shafqat
Hammad Afzal
Publication date
29-05-2018
Publisher
Springer US
Published in
Telecommunication Systems / Issue 1/2019
Print ISSN: 1018-4864
Electronic ISSN: 1572-9451
DOI
https://doi.org/10.1007/s11235-018-0472-y

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