网络安全中的入侵检测与防御系统研究 -计算机科学与技术专业

摘要

本文深入探讨了网络安全中的入侵检测与防御系统（IDS/IPS）的研究现状、存在问题及优化策略。随着网络技术的飞速发展，网络安全威胁日益严峻，传统的入侵检测与防御手段已难以满足当前复杂多变的网络环境需求。本文首先概述了入侵检测系统的定义、分类及技术原理，并分析了入侵防御系统的实现方式。随后，针对当前IDS/IPS在应用中普遍存在的误报与漏报问题、应对新型攻击手段能力不足、性能瓶颈与可扩展性受限以及协同防御能力薄弱等挑战进行了详细剖析。为应对这些问题，本文提出了多项优化措施，包括优化检测算法与规则集、加强情报共享与快速响应机制、采用分布式架构与资源优化策略，以及加强系统集成与联动等。具体而言，利用机器学习技术提升检测精度，动态更新与自适应规则集，引入行为分析增强识别能力；建立跨组织的情报共享平台，实现实时威胁情报订阅与更新，并利用区块链技术保障情报安全共享；采用分布式数据处理与微服务架构提升系统可扩展性和资源利用效率；整合多源数据与异构系统，建立统一的事件管理和响应平台，设计标准化接口以促进模块间协同工作。这些优化策略对于提升网络安全防护能力、降低安全风险具有重要意义。

关键词：网络安全；入侵检测系统（IDS）；入侵防御系统（IPS）；机器学习；分布式架构

Abstract

This paper discusses the research status, existing problems and optimization strategies of intrusion detection and prevention system (IDS/IPS) in network security. With the rapid development of network technology, network security threats are increasingly severe, and traditional intrusion detection and defense methods are difficult to meet the needs of the current complex and changeable network environment. This paper first summarizes the definition, classification and technical principle of intrusion detection system, and analyzes the implementation of intrusion prevention system. Then, it analyzes in detail the problems of false positives and missing positives, insufficient ability to deal with new attack methods, performance bottleneck and scalability limitation, and weak cooperative defense ability of IDS/IPS in application. In order to solve these problems, this paper proposes a number of optimization measures, including optimizing detection algorithm and rule set, strengthening intelligence sharing and rapid response mechanism, adopting distributed architecture and resource optimization strategy, and strengthening system integration and linkage. Specifically, machine learning technology is used to improve the detection accuracy, dynamic update and adaptive rule set, and behavioral analysis is introduced to enhance the recognition ability. Establish a cross-organization intelligence sharing platform, realize real-time threat intelligence subsc ription and update, and use blockchain technology to ensure intelligence security sharing; Distributed data processing and microservice architecture are adopted to improve system scalability and resource utilization efficiency. Integrate multi-source data and heterogeneous systems, establish a unified event management and response platform, and design standardized interfaces to promote collaboration between modules. These optimization strategies are of great significance for improving network security protection capabilities and reducing security risks.

Key words: Network security; Intrusion detection System (IDS); Intrusion prevention system (IPS); Machine learning; Distributed architecture

中文摘要 I

英文摘要 II

目录 III

引言 1

第1章、相关概念及理论基础 2

1.1、入侵检测系统的定义与分类 2

1.2、入侵检测技术原理 2

1.3、入侵防御系统的实现方式 2

第2章、当前入侵检测与防御系统存在的问题 4

2.1、误报与漏报问题 4

2.2、应对新型攻击手段的能力不足 4