计算机技术与发展Issue(2)：87-90,4.DOI:10.3969/j.issn.1673-629X.2016.02.020
云环境下基于改进BP算法的入侵检测模型
Intrusion Detection Model Based on Improved BP Algorithm in Cloud Environment
摘要
Abstract
With the development of cloud computing technology,the cost of commercial cloud resources is lower and lower,a malicious user could use the cloud resources in the same virtual machine or other cloud platform to implement intrusion attack. The intrusion attack for cloud service mainly includes the virtual machine or monitor attack and back channel attack. The existing cloud intrusion detection systems can only detect known attacks,cannot be applied to a virtualized environment that has different network models,and the detection accuracy of variant of attack is lower. Based on the analysis of the KVM network structures,an improved intrusion detection model based on BP algorithm in the cloud environment ( MBPCIDM) was proposed. It combines the ability of searching global optimal solution of PSO algorithm and the feature of the gradient descent in local search of BP algorithm. To make the BP network convergence faster and prevent it from falling into local optimum,the momentum and adaptive learning rate method was also used in this paper. The experimental results show that the average detection rate of the proposed model is higher,it can provide intrusion detection services for cloud environ-ments.关键词
云安全/入侵检测/内核虚拟机/反向传播神经网络/粒子群优化算法Key words
cloud security/intrusion detection/KVM/BP neural network/PSO algorithm分类
信息技术与安全科学引用本文复制引用
何文河,李陶深,黄汝维..云环境下基于改进BP算法的入侵检测模型[J].计算机技术与发展,2016,(2):87-90,4.基金项目
国家自然科学基金资助项目(61363067) （61363067）
广西自然科学基金资助项目(2012GXNSFAA053226) （2012GXNSFAA053226）
