基于量子神经网络的启发式网络隐蔽信道检测模型

摘要

In order to improve the detection rate of the covert channel, this paper discussed the covert channel detection technique , and gave a detail contrast research of related characters. Through the induction and analysis for the characteristics of network covert channel, this paper found some attributes to describe the network covert channels, and proposed an identification method based on network communication fingerprint. The communication fingerprints of covert channel were summarized such as in the protocol field, statistical regularities and behavior characteristics. On that basis, it designed and implemented a heuristic detection model of covert channel based on quantum neural network. Test results indicate that the system runs efficient and the results are more accurate.%为了提高隐蔽信道的检测率,讨论了传统的隐蔽信道检测技术的原理并对其特点作了详细的对比研究；通过对网络隐蔽通道特点的归纳和分析,找到可以描述网络隐蔽通道的若干属性,并提出基于网络隐蔽通道特征指纹的检测思想,归纳出隐蔽信道在协议域、统计规律、行为特征等方面表现出的通信指纹信息,在此基础上,设计并实现了一个基于量子神经网络的启发式网络隐蔽信道检测模型.测试结果表明该检测模型运行高效、检测结果较准确.