Intrusion detection method, system and device and readable storage medium

Abstract

The embodiment of the invention discloses an intrusion detection method, system and device and a readable storage medium, and the method comprises the steps: replacing a convolution layer with a full connection layer through a DRN residual block structure, simplifying a network structure, and accelerating a training process; moving an activation function layer after the jump layer connection to the activation function layer before the jump layer connection, so that the problems of gradient disappearance, gradient explosion and network degradation are more effectively solved; in order to improve the generalization ability of a SAE-DRN detection algorithm, using the EBAS to optimize the number of network layers of the SAE-DRN algorithm and the number of neurons in each layer of neural network. In order to prevent the EBAS algorithm from falling into local optimum, an omnibearing variable step size search algorithm, an optimal position updating strategy and a backtracking type step size updating rule are designed. Experimental results show that the SAE-DRN intrusion detection algorithm can well adapt to various intrusion detection data sets, the accuracy, precision, recall rate and F1 value of intrusion detection are effectively improved, and the misjudgment rate of intrusion detection is reduced.

Description

technical field [0001] The embodiments of the present application relate to the technical field of artificial intelligence, and specifically relate to an intrusion detection method, system, device, and readable storage medium. Background technique [0002] With the rapid development of network technology, computer viruses and network intrusions come one after another, bringing great challenges to network security. With the continuous improvement of the attacker's technical level, network attacks are becoming more and more hidden, and the harm they bring is also increasing. How to discover and defend against network attacks has become the core problem faced by network security personnel. Intrusion Detection System (IDS) can effectively identify abnormal intrusion information through network data analysis, and then intercept the intrusion data, greatly reducing the success rate of network attacks. Different from other network security systems, IDS is an active network securit...

AI Technical Summary

Problems solved by technology

However, traditional methods generally have shortcomings such as noise data sensitivity, overfitting, and high algorithm complexity, and some methods have weak generalization ability, which makes it difficult to adapt to the differences and changes in network attack types and attack methods.

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