Phd Proposal Investigation of Primary User Emulation Attack in Cognitive Radio Networks Chao Chen Department of Electrical & Computer Engineering Stevens Institute of Technology Hoboken, NJ 07030 5/15/2018

Outline Background Cognitive radio technology Security issues in cognitive radios Spectrum sensing in cognitive radios Primary user emulation attack Cooperative sensing in the presence of primary user emulation attack Cooperative sensing in the presence of PUEA with channel estimation error Cooperative sensing with multiple PUE attackers Cooperative Sensing with multiple antennas in the presence of PUEA Conclusion and future work 5/15/2018

Background Wireless communication system design requires higher data rate and larger channel capacity as well as better quality of service and spectrum utilization efficiency to meet the needs of wireless users. Security issues have drawn much research attention in wireless communications due to its “open air” nature. 5/15/2018

Cognitive Radio Technology Motivation 1. Frequency spectrum —— a scarce resource Primary user Secondary user Figure 1. Frequency allocation chart in US as of 2003 5/15/2018

Cognitive Radio Technology Motivation 2. Spectrum access is a more significant problem than spectrum scarcity. Figure 2. Measurements of spectrum utilization in downtown Berkeley 5/15/2018

Cognitive Radio Technology Definition Cognitive radio [1] is a technology of wireless communications in which a network or a user flexibly changes its transmitting or receiving parameters to achieve more efficient communication performance without interfering with licensed or unlicensed users. 1. J. Mitola and G. Maguire, “Cognitive radio: Making software radios more personal,” IEEE Communication Magazine, vol. 6, no. 4, pp. 13–18, Aug. 1999. 5/15/2018

Cognitive Radio Technology Spectrum holes Figure 3. Illustration of spectrum holes 5/15/2018

Cognitive Radio Technology Advances of cognitive radios J. Mitola I. Akyildiz S. Haykin Q. Zhao 5/15/2018

Cognitive Radio Technology Main functions 5/15/2018

Cognitive Radio Technology Cognitive cycle 5/15/2018

Security Issues in CR Networks Challenges The intrinsic properties of cognitive radio paradigm produce new threats and challenges to wireless communications [2]. Spectrum occupancy failures; Policy failures; Location failures; Sensor Failures; Transmitter/Receiver failures; Operating system disconnect; Compromised cooperative CR; Common control channel attacks. 2. T. Brown and A. Sethi, “Potential cognitive radio denial-of-service vulnerabilities and protection countermeasures: A multidimensional analysis and assessment,” IEEE International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom), Aug. 2007, pp. 456-464. 5/15/2018

Spectrum Sensing in Cognitive Radios Definition Spectrum sensing is to obtain awareness about the spectrum usage and existence of primary users in a geographical area. 5/15/2018

Spectrum Sensing in Cognitive Radios Spectrum opportunity Figure 4. Multiple dimensional spectrum opportunity 5/15/2018

Spectrum Sensing in Cognitive Radios A classical signal detection problem channel gain noise primary signal 5/15/2018

Spectrum Sensing in Cognitive Radios Spectrum sensing methods Spectrum sensing Transmitter detection Matched filter detection Energy detection Cyclostationary detection Cooperative detection Interference temperature detection 5/15/2018

Spectrum Sensing in Cognitive Radios Transmitter detection 1) Matched filter detection Advantages: Better detection performance and less time to achieve processing gain Disadvantages: Priori knowledge of primary signal is required (such as pilots, preambles or synchronized messages). 5/15/2018

Spectrum Sensing in Cognitive Radios Transmitter detection 2) Energy detection Decision statistic Y follows Chi-square distribution 5/15/2018

Spectrum Sensing in Cognitive Radios Transmitter detection 2) Energy detection False alarm probability and detection probability is decision threshold 5/15/2018

Spectrum Sensing in Cognitive Radios Transmitter detection 3) Cyclostationary detection Exploits built-in periodicity of modulated signals couple with sine wave carriers, hopping sequences, cyclic prefixes and etc. Advantages: better performance than energy detection Disadvantages: more computational complexity and longer observation time. 5/15/2018

Spectrum Sensing in Cognitive Radios Cooperative detection Figure 5. Transmitter detection problem 5/15/2018

Spectrum Sensing in Cognitive Radios Cooperative detection Figure 6. Cooperative detection model 5/15/2018 21

Spectrum Sensing in Cognitive Radios Cooperative detection Fusion rules: Hard combination (1 bit): AND rule, OR rule, majority rule … Soft combination (n bits): soft sensing information (e.g., signal energy) [3]. 3. J. Ma, G. Zhao, and Y. Li, “Soft combination and detection for cooperative spectrum sensing in cognitive radio networks,” IEEE Transactions on Wireless Communications, vol. 7, no. 11, pp. 4502 – 4507, Nov. 2008. 5/15/2018

Spectrum Sensing in Cognitive Radios Interference temperature detection Figure 7. Interference temperature detection 5/15/2018

Spectrum Sensing in Cognitive Radios Challenges Hardware requirement Hidden primary user problem Primary users detection in spread spectrum Detection capability Decision fusion in cooperative detection Security issues 5/15/2018

Primary User Emulation Attack Definition An attacker occupies the unused channels by emitting a signal with similar form as the primary user’s signal so as to prevent other secondary users from accessing the vacant frequency bands [4]. 4. R. Chen, J. Park, and J. Reed, “Defense against primary user emulation attacks in cognitive radio networks,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 25–37, Jan. 2008. 5/15/2018

Primary User Emulation Attack Detection of PUEA Distance ratio test & distance difference test Wald’s sequential probability ratio test 5/15/2018

Primary User Emulation Attack Defense against PUEA Localization based transmitter verification procedure Channel identification Dogfight and blind dogfight 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA System model 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA System model The signal received by the ith secondary user at the kth time instant is : primary user’s signal with power Pp : attacker’s signal with power Pm : channel gain between primary and ith secondary user : channel gain between attacker and ith secondary user 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA System model The combined signal in the fusion center at the kth time instant is, 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA System model When there is a PUEA, i.e., β = 1, the detection problem is reformulated as, After energy detector, 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Optimal combining scheme Objective: To design optimal weights to maximize the detection probability under the constraint of a prefixed false alarm probability where 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Optimal combining scheme Assumption: Block fading k is omitted in and For given and , the combined signal is also a complex Gaussian distributed random variable, where, 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Optimal combining scheme Decision statistic Y is compliant with central chi square distribution for both H0 and H1, And Pd and Pf are expressed as, 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Optimal combining scheme Optimization objective: where Quadratic form 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Optimal combining scheme Optimal solution: is the largest eigenvalue of 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Optimal combining scheme Remarks: 1) if Pm = 0, 2) virtual antenna array 3) average detection probability over fading channel MRC 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Optimal combining scheme Remarks: 4) acquisition of channel information a. priori knowledge such as pilots, synchronization messages, preambles... b. blind channel estimation 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Simulation results (b) N = 4 (a) N = 2 N is the number of secondary user 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Simulation results (c) N = 6 (d) N = 8 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA Simulation results 5/15/2018 41

Cooperative Spectrum Sensing in the Presence of PUEA Different network scenarios of PUEA for two users case 5/15/2018 42

Cooperative Spectrum Sensing in the Presence of PUEA Simulation results 5/15/2018 43

Cooperative Spectrum Sensing in the Presence of PUEA with Channel Estimation Error System model estimation error 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA with Channel Estimation Error System model 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA with Channel Estimation Error Average detection probability 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA with Channel Estimation Error Simulation results 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA with Channel Estimation Error Simulation results 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA with Channel Estimation Error Simulation results 5/15/2018

Cooperative Spectrum Sensing in the Presence of PUEA with Channel Estimation Error Simulation results 5/15/2018

Cooperative Spectrum Sensing in the Presence of Multiple PUE Attackers System model 5/15/2018

Cooperative Spectrum Sensing in the Presence of Multiple PUE Attackers System model The signal received by the ith secondary user at the kth time instant is 5/15/2018

Cooperative Spectrum Sensing in the Presence of Multiple PUE Attackers Optimal weights 5/15/2018

Cooperative Spectrum Sensing in the Presence of Multiple PUE Attackers Simulation results (a) K = 2 (a) K = 4 5/15/2018

Cooperative Spectrum Sensing in the Presence of Multiple PUE Attackers Simulation results (c) K = 6 (d) K = 8 5/15/2018

Cooperative Spectrum Sensing in the Presence of Multiple PUE Attackers Normalized attacking power 5/15/2018

Cooperative Spectrum Sensing with Multiple Antennas in the Presence of PUEA Multiple antenna technology 5/15/2018

Cooperative Spectrum Sensing with Multiple Antennas in the Presence of PUEA System model 5/15/2018

Cooperative Spectrum Sensing with Multiple Antennas in the Presence of PUEA System model The received signal at ith user at the kth detection instant is, the final combined signal at the fusion center is given as, 5/15/2018

Cooperative Spectrum Sensing with Multiple Antennas in the Presence of PUEA 5/15/2018

Cooperative Spectrum Sensing with Multiple Antennas in the Presence of PUEA Simulation results (a) 2 antenna case 5/15/2018

Cooperative Spectrum Sensing with Multiple Antennas in the Presence of PUEA Simulation results (b) 3 antenna case 5/15/2018

Cooperative Spectrum Sensing with Multiple Antennas in the Presence of PUEA Simulation results (c) 4 antenna case 5/15/2018

Conclusion Conclusion We have studied the cooperative spectrum sensing in CR network in the presence of primary user emulation attack. Through the proposed optimal combination scheme, the detection probability of the spectrum hole is optimized under the constraint of a required false alarm probability. Simulation results show the detection performance improvement of the proposed optimal combining scheme over the conventional MRC method. 5/15/2018

Conclusion Conclusion Investigation of the detection performance when the channel estimation error is considered in the proposed scheme. Investigation of the detection performance when multiple PUE attackers are considered in the network scenario. 5/15/2018

Publication Chao Chen, Hongbing Cheng, Yu-Dong Yao, “Cooperative Spectrum Sensing in the Presence of Primary User Emulation Attack in Cognitive Radio Networks”, under 2nd round review of IEEE transactions on wireless communications. 5/15/2018

Thank you! 5/15/2018