Cooperative Spectrum Sensing And Security Mechanisms For Cognitive Radio Sensor Networks

With features of low-power, low-cost, easy to deploy and self-organization, wireless sensor networks(WSNs) have been widely used monitoring of sensitive information in diverse fields such as military, environment, household and industrial. Cognitive radio sensor networks(CRSNs) utilize the dynamic spectrum access to improve the utilization of the precious radio spectrum resource. The performance of cooperative spectrum sensing which is the fundamental technique matters in CRSNs.Radio Environment Map(REM) provides more information for opportunistically access and interference control in CRSNs. Thus, in this thesis, we deal with the distributed consensus algorithm for cooperatively estimating REM. We also study the security problem against data falsification attack to assure accurate estimation result.Based on basis function expansion and exploiting the sparsity of preselected bases,we formulate the estimation process as a LS problem with an L1-norm constraint. This formulation enables automatically model selection to improve the estimation accuracy. A distributed consensus algorithm is then presented using alternating direction method of multipliers(ADMM) after decoupling the problem into each sensor node.Simulation results illustrate the effective of the proposed algorithm.A two-tier secure scheme is proposed to obtain accurate REM estimation result in the presence of data falsification attacks. The data selection tier relies on using trusted sensors to evaluate the trustworthiness of all sensors and then select the effective data set. A secure data processing tier is then followed to provide fine-grained malicious data detection and to eliminate the effect of these data. Our scheme enable robust estimation result only if the normal data consist of enough information. The efficacy and efficiency of our scheme have been confirmed by simulation studies.