MLP算法在网络入侵检测中的应用与性能评估

Application and Performance Evaluation of Deep Learning Algorithms in Network Intrusion Detection

由于网络攻击日益复杂,需要采用准确、高效的网络入侵检测技术来确保信息安全,深度学习算法作为强大的网络入侵检测工具受到了人们的广泛关注。文章首先分析传统入侵检测方法存在的问题,其次介绍多层次感知器(Multi-Layer Perceptron,MLP)入侵检测算法的基本原理和优化方法,最后通过实验分析验证深度学习算法在网络入侵检测中的有效性,以期为进一步加强网络安全提供有力支持。

As network attacks become increasingly complex,accurate and rapid network intrusion detection technology is required to ensure information security.Deep learning algorithms have received widespread attention as a powerful network intrusion detection tool.This article first analyzes the problems existing in traditional intrusion detection methods,secondly introduces the basic principles and optimization methods of the Multi-Layer Perceptron(MLP)intrusion detection algorithm,and finally verifies the use of deep learning algorithms in network intrusion detection through experimental analysis effectiveness,in order to provide strong support for further strengthening network security.