CAJ | 학술논문

异常检测技术能够检测到未知攻击,对于保障无线传感器网络安全具有重要意义。当前的异常检测技术实时性差,误报率高且计算量大,因此,无法直接应用在无线传感器网络中。鉴于此,提出基于小波分析的实时无线传感网异常检测( Wavelet Analysis-Based Real-time Anomaly Detection,WARAD)算法。在整个检测过程中, WARAD算法采用了逆向获取实时网络流量,然后通过对小尺度区间使用小波系数方差法计算Hurst值,从而提高异常检测的实时性、准确率,并降低求解Hurst值的运算复杂度。最后,在MeshIDE平台上实现了基于WARAD算法的异常检测系统,实验结果表明此算法极大地提高了无线传感网环境下异常检测的实时性,并降低了异常检测的误报率和漏报率。
이상검측기술능구검측도미지공격,대우보장무선전감기망락안전구유중요의의。당전적이상검측기술실시성차,오보솔고차계산량대,인차,무법직접응용재무선전감기망락중。감우차,제출기우소파분석적실시무선전감망이상검측( Wavelet Analysis-Based Real-time Anomaly Detection,WARAD)산법。재정개검측과정중, WARAD산법채용료역향획취실시망락류량,연후통과대소척도구간사용소파계수방차법계산Hurst치,종이제고이상검측적실시성、준학솔,병강저구해Hurst치적운산복잡도。최후,재MeshIDE평태상실현료기우WARAD산법적이상검측계통,실험결과표명차산법겁대지제고료무선전감망배경하이상검측적실시성,병강저료이상검측적오보솔화루보솔。
Anomaly detection can detect new and unknown attacks,which has great significance on the wireless sensor networks security. Nowadays,the proposed anomaly detection schemes has poor real-time,high false positive rate and the large amount of computational overhead, and hence the schemes are not suitable for wireless sensor networks. In this paper,a wavelet analysis-based real-time anomaly detection ( Wavelet Analysis-based Real-time Anomaly Detection, WARAD) algorithm for wireless sensor network is proposed. Throughout the detecting process, the WARAD algorithm reversely collects the real-time network traffic,and then uses the variance of the wavelet coefficients in the small-scale interval to compute the Hurst values,which can improve the real-time and the accuracy of anomaly detection,and reduce the computational complexity of solving the Hurst values. Finally,the WARAD algorithm-based intrusion detection system is implemented on the platform of MeshIDE. The experimental results showed that the proposed algorithm greatly improved the real-time of anomaly detection for wireless sensor networks,and reduced the false positive rate and the false negative rate of anomaly detection.