计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
9期
90-93
,共4页
混沌粒子群优化算法%最小二乘支持向量机%网络异常%检测
混沌粒子群優化算法%最小二乘支持嚮量機%網絡異常%檢測
혼돈입자군우화산법%최소이승지지향량궤%망락이상%검측
Chaos Particle Swarm Optimization algorithm(CPSO)%Least Squares Support Vector Machine(LSSVM)%network intrusion%detection
网络攻击具有多样性和隐蔽性,为了提高网络安全性入侵检测的正确率,提出一种混沌粒子群算法(CPSO)和最小二乘支持向量机(LSSVM)相融合的网络入侵检测方法(CPSO-LSSVM).利用混沌粒子群算法对 LSSVM 模型参数进行搜索,选择 LSSVM 最优参数,采用 KDDCUP99数据集对 CPSO-LSSVM 性能进行测试,实验结果表明,CPSO-LSSVM 提高了网络入侵检测正确率,降低了误报率,可以为网络安全提供有效保证.
網絡攻擊具有多樣性和隱蔽性,為瞭提高網絡安全性入侵檢測的正確率,提齣一種混沌粒子群算法(CPSO)和最小二乘支持嚮量機(LSSVM)相融閤的網絡入侵檢測方法(CPSO-LSSVM).利用混沌粒子群算法對 LSSVM 模型參數進行搜索,選擇 LSSVM 最優參數,採用 KDDCUP99數據集對 CPSO-LSSVM 性能進行測試,實驗結果錶明,CPSO-LSSVM 提高瞭網絡入侵檢測正確率,降低瞭誤報率,可以為網絡安全提供有效保證.
망락공격구유다양성화은폐성,위료제고망락안전성입침검측적정학솔,제출일충혼돈입자군산법(CPSO)화최소이승지지향량궤(LSSVM)상융합적망락입침검측방법(CPSO-LSSVM).이용혼돈입자군산법대 LSSVM 모형삼수진행수색,선택 LSSVM 최우삼수,채용 KDDCUP99수거집대 CPSO-LSSVM 성능진행측시,실험결과표명,CPSO-LSSVM 제고료망락입침검측정학솔,강저료오보솔,가이위망락안전제공유효보증.
Network attack has diversity and concealment. In order to improve the security of network abnormal intrusion detec-tion accuracy, this paper proposes a network anomaly detection method based on Chaos Particle Swarm Optimization algorithm (CPSO)and least square support vector machine. The parameters of LSSVM are optimized by CPSO to select the optimal parameters of LSSVM, and the CPSO-LSSVM performance is tested by KDD CUP99 data. The experimental results show that the proposed method has improved the network anomaly detection accuracy, and reduced the false alarm rate. It can provide an effective guarantee for network security.
