基于身份加密的智慧校园网络入侵检测系统

Smart Campus Network Intrusion Detection System Based on Identity Encryption

目前已有校园网络入侵检测系统的平均误报率高、平均漏报率高、平均延时高。基于此提出基于身份加密的智慧校园网络入侵检测系统,在Snort规则的基础上,系统主要结构包括探测器模块、数据存储中心、管理控制中心,利用校园网络流量和校园网络防火墙联动实现自动化入侵检测。以IBE公钥加密为基础加密用户身份,实现智慧校园网络入侵检测系统。实验结果表明,该方法在降低漏报率的情况下更好地提高校园网络入侵检测效率,提高捕获数据包的效率,系统的平均误报率低、平均漏报率低、平均延时低。

At present, the existing campus network intrusion detection system has high average false alarm rate, high average false alarm rate and high average delay. Based on this, the intelligent campus network intrusion detection system based on identity encryption is proposed. Based on snort rules, the main structure of the system including detector module, data storage center and management control center. The automatic intrusion detection is realized by the linkage of campus network traffic and campus network firewall. IBE public key encryption is used to encrypt the user’s identity to realize the intelligent campus network intrusion detection system. The experimental results show that this method can improve the efficiency of campus network intrusion detection and capture data packets, and the average false alarm rate, average false alarm rate and average delay of the system are low.