摘要
针对目前的入侵检测技术误警率和漏警率较高，提出了一个优化的贝叶斯算法，通过引入滑动窗口技术改善入侵检测的实时性。该文利用贝叶斯优化算法对对Probe、DoS、U2R、R2L测试集进行实验仿真比较，结果表明：该算法能很好完成入侵检测分类：该算法能提高入侵检测正确率。
As the erroneous of the present immersion and examining technology occur frequently, the author of this paper puts forward a Bayesian Optimization Algorithm, aiming to introduce the practicable method of a sliding window technology and improve this examining shill. By means of Bayesian Optimization Algorithm, the author intends to compare the experiment of Probe, DoS, UaR, R2L. Conse- quently, this method can complete the classification of the immersion and examination, meanwhile improving the ratio of correctness.
作者
蒲石
PU Shi （The Modem Technological Center of Neijiang Normal University, Neijiang 641112, China）
出处
《电脑知识与技术》
2010年第01X期696-697,700,共3页
Computer Knowledge and Technology
关键词
贝叶斯优化算法
入侵检测
分类
bayesian optimization algorithm
immersion and examining
classification
