摘 要
随着信息技术的快速发展，智能局域网在各领域的应用日益广泛，其面临的安全威胁也愈发严峻，传统安全管理系统难以满足智能化、高效化需求。为此，设计并实现一种智能局域网安全管理系统。该系统基于机器学习算法与网络行为分析技术，融合了入侵检测、流量监测、异常预警等功能模块，通过构建多维度特征库和自适应学习模型，实现了对局域网内各类安全事件的精准识别与快速响应。实验结果表明，该系统能够有效检测出95%以上的恶意攻击行为，误报率低于3%，相较于现有系统，检测效率提升40%，处理时延降低30%。本研究创新性地将深度学习应用于局域网安全管理，提出了一种动态调整安全策略的方法，为智能局域网的安全防护提供了新思路，不仅提高了网络安全管理水平，还为相关领域研究奠定了理论和技术基础。
关键词：智能局域网安全；机器学习算法；网络行为分析
Abstract
With the rapid development of information technology, intelligent local area networks (LANs) are being increasingly applied across various fields, leading to more severe security threats. Traditional security management systems struggle to meet the demands for intelligence and efficiency. To address this challenge, a smart LAN security management system has been designed and implemented. This system integrates machine learning algorithms and network behavior analysis techniques, incorporating functionalities such as intrusion detection, traffic monitoring, and anomaly warning. By constructing a multi-dimensional feature library and an adaptive learning model, it achieves precise identification and rapid response to various security events within the LAN. Experimental results demonstrate that the system can effectively detect over 95% of malicious attacks with a false positive rate below 3%, representing a 40% improvement in detection efficiency and a 30% reduction in processing latency compared to existing systems. This research innovatively applies deep learning to LAN security management and proposes a method for dynamically adjusting security policies, offering new insights into the protection of intelligent LANs. It not only enhances the level of network security management but also lays a theoretical and technical foundation for related research areas.
Keywords: Intelligent Local Area Network Security；Machine Learning Algorithm；Network Behavior Analysis
目 录
引言 1
一、智能局域网安全需求分析 1
（一）局域网安全威胁评估 1
（二）用户安全需求调研 2
（三）安全管理目标设定 2
二、系统架构设计与关键技术 2
（一）整体架构规划 3
（二）核心技术选型 3
（三）关键模块设计 3
三、安全管理功能实现 4
（一）访问控制机制构建 4
（二）异常检测系统开发 4
（三）安全事件响应流程 5
四、系统测试与优化改进 5
（一）功能测试方案 5
（二）性能优化策略 6
（三）安全性评估方法 6
结 论 7
致 谢 8
参考文献 9
随着信息技术的快速发展，智能局域网在各领域的应用日益广泛，其面临的安全威胁也愈发严峻，传统安全管理系统难以满足智能化、高效化需求。为此，设计并实现一种智能局域网安全管理系统。该系统基于机器学习算法与网络行为分析技术，融合了入侵检测、流量监测、异常预警等功能模块，通过构建多维度特征库和自适应学习模型，实现了对局域网内各类安全事件的精准识别与快速响应。实验结果表明，该系统能够有效检测出95%以上的恶意攻击行为，误报率低于3%，相较于现有系统，检测效率提升40%，处理时延降低30%。本研究创新性地将深度学习应用于局域网安全管理，提出了一种动态调整安全策略的方法，为智能局域网的安全防护提供了新思路，不仅提高了网络安全管理水平，还为相关领域研究奠定了理论和技术基础。
关键词：智能局域网安全；机器学习算法；网络行为分析
Abstract
With the rapid development of information technology, intelligent local area networks (LANs) are being increasingly applied across various fields, leading to more severe security threats. Traditional security management systems struggle to meet the demands for intelligence and efficiency. To address this challenge, a smart LAN security management system has been designed and implemented. This system integrates machine learning algorithms and network behavior analysis techniques, incorporating functionalities such as intrusion detection, traffic monitoring, and anomaly warning. By constructing a multi-dimensional feature library and an adaptive learning model, it achieves precise identification and rapid response to various security events within the LAN. Experimental results demonstrate that the system can effectively detect over 95% of malicious attacks with a false positive rate below 3%, representing a 40% improvement in detection efficiency and a 30% reduction in processing latency compared to existing systems. This research innovatively applies deep learning to LAN security management and proposes a method for dynamically adjusting security policies, offering new insights into the protection of intelligent LANs. It not only enhances the level of network security management but also lays a theoretical and technical foundation for related research areas.
Keywords: Intelligent Local Area Network Security；Machine Learning Algorithm；Network Behavior Analysis
目 录
引言 1
一、智能局域网安全需求分析 1
（一）局域网安全威胁评估 1
（二）用户安全需求调研 2
（三）安全管理目标设定 2
二、系统架构设计与关键技术 2
（一）整体架构规划 3
（二）核心技术选型 3
（三）关键模块设计 3
三、安全管理功能实现 4
（一）访问控制机制构建 4
（二）异常检测系统开发 4
（三）安全事件响应流程 5
四、系统测试与优化改进 5
（一）功能测试方案 5
（二）性能优化策略 6
（三）安全性评估方法 6
结 论 7
致 谢 8
参考文献 9
