Information Security Coding Rule Based on Neural Network and Greedy Algorithm and Application in Network Alarm Detection

Abstract

With the development of computer network, network information resources have brought great convenience to users. However, the security problems of computer network have become increasingly prominent, and the main threat is the invasion of the information system through the network. Network intrusion will bring great losses to society, especially to the government and military agencies. With the increase of network intrusion, the firewall can't resist the attack on the network. Intrusion detection system makes up the shortcomings of traditional Internet security technology, and it is a kind of active defense technology. Through security log, audit data and other information, intrusion detection system can detect the network attacks and take the corresponding measures. Intelligent intrusion detection system is a hot spot in the field of network security, commonly based on neural network, genetic algorithm, greedy algorithm, fuzzy technology, and so on. In this paper, we apply the neural network and the greedy algorithm into the network security detection system. We analyze the theories of neural network and greedy algorithm, and introduce the evaluation model of network security system. Experiments show that the information security coding rule based on neural network and greedy algorithm can help network monitoring system better detect the network attacks.