抵御恶意模拟主用户攻击的拟合优度检测算法

在认知无线电网络中,针对模拟主用户攻击(primary user emulation attack,PUEA),采用Anderson-Darling(AD)检验来代替传统的假设检验算法来提高系统性能.假设PUEA具有一定的可能性,通过计算接收到的信道数据样本分布函数与经验分布函数之间的Anderson-Darling距离,调整相关参数来确定阈值,并与距离比较,实现频谱检测,有效防止恶意主用户攻击.仿真结果表明,与能量检测相比,系统性能优化了能量检测器的改进.

A goodness-of-fit detection algorithm for countering the primary user emulation attack

In the cognitive radio network,for countering the primary user emulation attack( PUEA),the Anderson-Darling test is used to replace the traditional hypothesis testing algorithm to improve the performance of the system. We assume that the PUEA has a certain probability. By calculating the AD distance between the distribution function of the received-data channel and the empirical distribution function,we adjust the correlation parameters to determine the threshold and compare the distances to achieve the spectrum detection,effectively preventing the Malicious host user attack. The simulation results show that the performance of this system improves the energy detector compared with the traditional energy detection.