Mitigating Multiple attacks in Cognitive Radio Networks


  • Sivasankari Jothiraj
  • Sridevi Balu



Location falsification attack, location proof verification, certificate authority, database-driven CRNs


Database driven CRNs are taken into consideration because the promising technique to enhance the wireless spectrum usage, it faces serious safety demanding situations via location cheating attack. The number one challenges are location proof verification and region solitude verification. Malicious users create a faux region with the aid of self-seeking the all to be had spectrum bands. A region based totally service is used for imparting provider to the consumer. Wi-Fi authority verifies the place whether or not the proof is legitimate or no longer. If the person is valid, it passes the facts to the base station. This technique provides effective reduction of malicious user in the cognitive radio community.




[1] International Telecommunications Union, “Estimated spectrum bandwidth requirements for the future development of IMT-2000 and IMT-Advanced,†ITU-R Report M.2078, 2006.

[2] FCC, ET Docket No 03-222 Notice of proposed rule making and order, December 2003.

[3] F.Akyildiz(2006),†NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey,Computer networks, Volume 50 Issue 13, Pages 2127-2159

[4] DARPA XG WG, The XG Architectural Framework V1.0, 2003.

[5] L. Lu, X. Zhou, U. Onunkwo, and G. Li, “Ten years of research in spectrum sensing and sharing in cognitive radio,†EURASIP J. Wirel. Commun. Netw., vol. 2012, no. 1, p. 28, 2012.

[6] S. Haykin(2005), “Cognitive Radio: Brain-Empowered Wireless Communications,†IEEE JSAC, vol. 23, no. 2, pp. 201–20

[7] A. Ghasemi, E.S. Sousa, Collaborative spectrum sensing for opportunistic access in fading environment, in: Proc. IEEE DySPAN 2005, November 2005, pp. 131–136.

[8] R.W. Thomas, L.A. DaSilva, A.B. MacKenzie, Cognitive networks, in: Proc. IEEE DySPAN 2005, November 2005, pp. 352–360.

[9] F.K. Jondral, Software-defined radio-basic and evolution to cognitive radio, EURASIP Journal on Wireless Communication and Networking 2005

[10] Akyildiz, I. F., Lo, B. F., & Balakrishnan, R. (2011). Cooperative spectrum sensing in cognitive radio networks: A survey. Physical Communication, 4(1), 40–62

[11] J. Unnikrishnan, V.V. Veeravalli, Cooperative sensing for primary detection in cognitive radio, IEEE Journal of Selected Topics in Signal Processing 2 (1) (2008) 18–27.

[12] Z. Li, F. Yu, M. Huang, A cooperative spectrum sensing consensus scheme in cognitive radios, in: Proc. of IEEE Infocom 2009, 2009, pp. 2546–2550.

[13] B. Wild, K. Ramchandran, Detecting primary receivers for cognitive radio applications, in: Proceedings of the IEEE DySPAN 2005, November 2005, pp. 124–130.

[14] W. Zhang, K. Letaief, Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks— [transaction letters], IEEE Transactions on Wireless Communications 7 (12) (2008) 4761–4766.

[15] S. Alrabaee, M. Khasawneh, A. Agarwal, N. Goel, and M. Zaman, “Applications architectures and protocol design issues for cognitive radio networks: a survey,†International Journal of Wireless and Mobile Computing, vol. 7, no. 5, pp. 415–427, 2014.

[16] Zeng, Kexiong, et al. “Location spoofing attack and its countermeasures in database-driven cognitive radio networks.†Communications and Network Security (CNS), IEEE, 2014.

[17] Li, Muyuan, et al. “All your location is belong to us: Breaking mobile social networks for automated user location tracking.†ACM Mobile Hoc. ACM, 2014.

[18] Jiajia Liu, Shangwei Zhang, Nei Kato, et al. “Device-to-device communications for enhancing quality of experience in software defined multitier LTE-A networks.†IEEE Network, 2015, 29(4):46-52.

View Full Article: