网络入侵反追踪节点最优路径推演平台的设计与实现

Design and implementation of optimal path inference platform for network intrusion anti-tracking node

无线传感网络内部节点攻击无法通过防御技术进行控制,对网络安全造成了极大的威胁。因此,设计并实现基于Web远程管理的网络入侵反追踪节点最优路径推演平台,对网络入侵反追踪节点进行准确检测,确保网络的安全性。该平台由核心控制模块、数据库模块以及检测模块构成。检测模块按照网络协议对接收的数据包进行分流操作、均衡网络负载。采用依据Libpcap库的通用数据捕获方法,采集网络中的原始数据,再依据规则模式匹配的规则检测模块,通过入侵事件描述语言,对规则库进行匹配,获取网络入侵节点,若入侵节点的信任值低于阈值,则为入侵反追踪节点。实验结果表明,所设计平台具有较低的误检率、较高的检测率以及较低的资源使用量,安全性能和空间性能较强。

As the wireless sensor network internal node attack can＇t be controlled by the defense technology, an optimal path inference platform based on Web remote management was designed and implemented for accurate detection of network intru- sion anti-tracking nodes to ensure the security of network. The platform consists of a core control module, database module and control module. The detection module shunts received packets according to network protocol to balance the network load. The common data capture method based on Libpcap library is used to collect the original data in the network. The rule base is matched with intrusion event description language based on rule detecting module for rule pattern matching to obtain network in- trusion node. If trust value of the invasion node is lower than the threshold, it will be invasion anti-tracking node. The experi- ment result shows that the design platform has low error detection rate, high detection rate, low resource usage, high safety per- formance and strong spacial performance.