计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
3期
85-88,123
,共5页
黄亮%吴帅%谭国律%郑军
黃亮%吳帥%譚國律%鄭軍
황량%오수%담국률%정군
网络入侵%相关向量机%参数选择%粒子群优化算法%精英选择策略
網絡入侵%相關嚮量機%參數選擇%粒子群優化算法%精英選擇策略
망락입침%상관향량궤%삼수선택%입자군우화산법%정영선택책략
network intrusion%relevance vector machine%parameters selection%particle swarm optimization algorithm%elite strategy
为了提高网络入侵检测的正确率,提出一种精英选择策略粒子群算法(EPSO)优化相关向量机(RVM)的网络入侵检测模型(EPSO-RVM)。将相关向量机的参数编码成粒子,将入侵检测正确率作为粒子群搜索的目标,通过粒子群算法对参数优化问题进行求解,并引入精英选择策略增强粒子群算法的全局搜索能力,根据最优参数建立基于RVM的入侵检测模型,采用KDD99数据集对其性能测试,结果表明,相对于对比模型,EPSO-RVM较好地解决了相关向量机参数优化难题,提高了网络入侵检测的正确率。
為瞭提高網絡入侵檢測的正確率,提齣一種精英選擇策略粒子群算法(EPSO)優化相關嚮量機(RVM)的網絡入侵檢測模型(EPSO-RVM)。將相關嚮量機的參數編碼成粒子,將入侵檢測正確率作為粒子群搜索的目標,通過粒子群算法對參數優化問題進行求解,併引入精英選擇策略增彊粒子群算法的全跼搜索能力,根據最優參數建立基于RVM的入侵檢測模型,採用KDD99數據集對其性能測試,結果錶明,相對于對比模型,EPSO-RVM較好地解決瞭相關嚮量機參數優化難題,提高瞭網絡入侵檢測的正確率。
위료제고망락입침검측적정학솔,제출일충정영선택책략입자군산법(EPSO)우화상관향량궤(RVM)적망락입침검측모형(EPSO-RVM)。장상관향량궤적삼수편마성입자,장입침검측정학솔작위입자군수색적목표,통과입자군산법대삼수우화문제진행구해,병인입정영선택책략증강입자군산법적전국수색능력,근거최우삼수건립기우RVM적입침검측모형,채용KDD99수거집대기성능측시,결과표명,상대우대비모형,EPSO-RVM교호지해결료상관향량궤삼수우화난제,제고료망락입침검측적정학솔。
In order to improve the detection precision of network intrusion, this paper proposes a novel network intrusion detection model based on relevance vector machine optimized by particle swarm optimization algorithm with elite election strategy. The parameters of relevance vector machine are encoded into particles, and network intrusion detection rate is taken as the search goal of particle swarms, and then particle swarm optimization algorithm is used to solve the parameters optimi-zation problem in which elite election strategy is introduced to improve the search performance. Network intrusion detec-tion model is established based on the optimal parameters of relevance vector machine, and the simulation experiments are carried out on the KDD99 dataset. The simulation results show that the proposed model has solved parameters optimi-zation problem of relevance vector machine and improved intrusion detection rate compared with reference models.