Network Security Situational Awareness Based on Genetic Algorithm in Wireless Sensor Networks

Abstract

How to design an effective and secure user authentication scheme suitable for complex wireless sensor network (WSN) environments has very important research significance. Based on the genetic algorithm theory, the paper constructs the security situational awareness model of wireless sensor network, and studies the WSN user security authentication scheme. The model uses the genetic algorithm extraction technology combined with the hash function to generate the biometric key, which solves the data accuracy problem of network security situational awareness: the user’s biometric key is obtained through the fuzzy extraction technology; the resistance of the node is to be attacked, but it is powerless when most of the nodes are broken, and it limits the scalability of the network. During the simulation process, the authentication of the identity of the cluster head by the base station is added in the topology establishment stage, and a one-way hash function and a shared key are added to the key management, so that the encryption key and the authentication key change periodically and dynamically, so that enhanced network communication security. The analysis results show that the protocol is feasible. The algorithm proposed in this paper reduces about 70% of the features in the original feature set, the classification detection rate is increased from 95.7212% to 97.7379%, and the false alarm rate is reduced from 7.9427% to 3.1072%, effectively improving the balance between safety and design cost.