Radio Jamming In Database-driven Cognitive Radio Networks:Attack And Countermeasures

White space database provides an efficient way for the SUs(Secondary Users)to obtain spectrum availability information by submitting a location based query in database-driven cognitive radio.However,white space database can also be exploited by the attackers to significantly enhance their jamming capability by taking advantage of the available channel information from spectrum database and blocking the SUs at an increased successful rate.The challenge is that the unique characteristics(e.g.,lack of the wide range frequencies or continuous broadband)make existing anti-jamming techniques(e.g.,Direct-Sequence Spread Spectrum and Frequency Hopping Spread Spectrum)difficult to be adopted in the considered network.In this study,We introduce Sequential Bayesian Jammer Inference to infer the likelihood of an SU being jammer based on the channels occupied by SUs even under the collusion attack performed by multiple jammers.Then we present a novel Jammer Inference based Jamming Defense framework(jDefender),which is comprised of anti-jamming on spectrum query phase including puzzle solving,channel allocation,and other anti-jamming strategies during the wireless transmission.The strength of the anti-jamming strategies(e.g.,puzzle difficulties)will be correlated with the possibility of an SU being a jammer to achieve the tradeoff between system performance and jamming tolerance.We implement the proposed solutions on Universal Software Radio Peripheral(USRP)and PC and extensive evaluations validate the effectiveness of the attacks and countermeasures.