基于SVDD的认知无线电网络仿冒主用户检测技术

Detecting the Primary User Emulation Based on SVDD in Cognitive Radio Networks

为了解决传统主用户感知技术无法检测认知无线电网络中的仿冒主用户(PUE)攻击问题,提出了一种基于支持向量数据描述(SVDD)的PUE检测方法。该方法将PUE攻击检测建模为一个数据不平衡的单类分类问题,采用高效的SVDD算法,在对PUE攻击一无所知的情况下,仅利用认知无线电网络中的合法用户数据训练单类分类器。将待测样本输入训练后的分类器即可实现PUE攻击检测。理论分析和仿真结果表明,利用该方法进行PUE攻击检测,可以获得较低的虚警率和漏检率。

To resolve the problem that traditional primary user sensing technique cannot detect PUE （Primary User Emulation） attack in cognitive radio networks,a novel detecting technique is put forward that based on SVDD （Support Vector Date Description）. Detecting PUE is modeled as a one-class imbalanced classified problem in this technique. Without PUE attack parameters,a one-class classifier is trained with legal users’ parameters by SVDD algorithm. Input the pending samples to the trained classifier,PUE will be detected. Analysis and simulation results show that,a lower false alarm probability and miss detection probability can be obtained.