基于高阶AR模型的网络异常检测
기우고계AR모형적망락이상검측
Network Anomaly Detection Based on High-order AR Model
  • 万方数据
    计算机工程 계산궤공정
    COMPUTER ENGINEERING
    2010年 3期 174-176 ,共3页

    黄强盛%程久军%康钦马

    황강성%정구군%강흠마

    网络异常检测%AR模型%遗传算法 網絡異常檢測%AR模型%遺傳算法
    망락이상검측%AR모형%유전산법
    network anomaly detection%AR model%genetic algorithm
    介绍基于1阶AR模型的检测方法,用高阶AR模型代替1阶AR模型以增加其精度.鉴于高阶AR模型最优参数的确定是个NP完全问题,利用遗传算法搜索其参数的近似最优解,通过实验验证高阶AR模型对网络异常检测的有效性和精确性.
    개소기우1계AR모형적검측방법,용고계AR모형대체1계AR모형이증가기정도.감우고계AR모형최우삼수적학정시개NP완전문제,이용유전산법수색기삼수적근사최우해,통과실험험증고계AR모형대망락이상검측적유효성화정학성.
    This paper presents detection method based on 1-order AR model.Because of the low precision 1-order AR model owns,it proposes a method by substituting high-order AR model for 1-order one to make it more precise.Because setting the best parameters of the high-order AR model is an NP-complete problem.it applies genetic algorithm tO search the beuer ones.Experiment shows that the high-order AR model is more efficient and precise for network anomaly detection.
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