Adaptive Optimization Parameter Simulated Annealing for Real time Monitoring of Node Intrusion in Wireless Communication Networks
The conventional intrusion monitoring methods for wireless communication network nodes mainly rely on intrusion feature matching.Most malicious code is mixed with legitimate code,which cannot meet the requirements of feature matching,resulting in false alarms and missed alarms in intrusion monitoring.Therefore,a real-time monitoring method for wireless communication network node intrusion using adaptive optimization parameter simulated annealing was designed.Set intrusion monitoring standards for wireless communication network nodes,and develop intrusion behavior monitoring discrimination standards for different network monitoring environments to ensure the effectiveness of intrusion behavior monitoring.Based on simulated annealing optimization,real-time monitoring parameters for communication network node intrusion are optimized.According to the state transition probability of the simulated annealing algorithm,the current node intrusion situation is determined to meet the real-time monitoring requirements for network node intrusion.Through comparative experiments,it was verified that the monitoring accuracy of this method is higher and can be applied in practical life.
adaptive optimization parameterssimulated annealingwireless communication network nodesinvasionreal time monitoring methods