Research Of Intrusion Detection Based On Hierarchical Structure In Wireless Sensor Networks

Wireless Sensor Networks consist of lots of micro sensor nodes deployed in monitored area,through wireless communication way,which build a multi-hop and self-organizational network system. WSN's destination is to apperceive, collect and process information of apperceived object in overlay area, then to send this information to observer. This thesis mainly focuses on research of intrusion detection in wireless sensor networks. After the second firewall, VPN, encryption and other traditional security, Intrusion detection is the next-generation information security technologies and proactive defense measure, which provides internal attacks and external attacks and misuse in real-time protection against the network before being intercepted and Response to invasion. How to use the appropriate intrusion detection technology, design efficient intrusion detection model to improve the detection rate of the entire system, and saving system power of wireless sensor networks has become a hot topic in this field.This paper firstly introduces the concepts of wireless sensor networks, then analysises the chassical intrusion detection techniques. Drawing one of the best ideas the paper puts forward an efficient intrusion detection model. The simulation results show that the model can improve the system detection rate, effective balancing energy load, saving energy of the system.The major innovations of this dissertation are as follows:1. in the wireless sensor network system formation process, the paper analyze and study the structure of wireless sensor network system and design one intrusion detection system architecture of hierarchy. This system is superb, easy to deploy and control, thus saving the entire system energy.2. in the proposed intrusion detection system, the paper using the principle of multi-node joint collaboration presents a highly efficient intrusion detection model, improving detection algorithm process. The simulation results show that the model can improve the system detection rate and the effective load-balanced energy, saving energy of the system.