摘要
随着智能网联汽车的快速发展，其信息安全问题日益凸显，成为制约产业健康发展的关键因素。本研究旨在系统分析智能网联汽车面临的安全威胁，并提出针对性的信息安全防护技术方案。通过结合车联网架构特点与潜在攻击路径，研究设计了一种多层次、多维度的综合防护框架，涵盖数据加密传输、入侵检测与防御以及隐私保护等核心技术。具体而言，基于对称加密算法与非对称加密算法的优化组合，实现了高效且安全的数据通信；同时引入深度学习模型以增强入侵检测系统的实时性和准确性，并通过差分隐私技术保障用户敏感信息的安全性。实验结果表明，所提出的防护技术在降低攻击风险、提升系统鲁棒性方面具有显著优势，能够在复杂网络环境下有效抵御多种类型的恶意攻击。此外，该研究创新性地将联邦学习应用于车载终端的安全更新机制中，解决了传统集中式更新模式带来的效率低下和隐私泄露问题。总体而言，本研究为智能网联汽车的信息安全防护提供了理论支持和技术参考，对推动行业标准化建设及实际应用落地具有重要意义。
关键词：智能网联汽车；信息安全防护；加密通信
Abstract
With the rapid development of intelligent connected vehicles, their information security issues have become increasingly prominent, becoming a key factor constraining the healthy development of the industry. This study aims to systematically analyze the security threats faced by intelligent connected vehicles and propose targeted information security protection technical solutions. By integrating the characteristics of the vehicular network architecture with potential attack paths, a multi-layer and multi-dimensional comprehensive protection fr amework is designed, encompassing core technologies such as encrypted data transmission, intrusion detection and defense, as well as privacy protection. Specifically, an optimized combination of symmetric and asymmetric encryption algorithms is employed to achieve efficient and secure data communication. Meanwhile, deep learning models are introduced to enhance the real-time performance and accuracy of intrusion detection systems, and differential privacy technology is utilized to ensure the security of user-sensitive information. Experimental results demonstrate that the proposed protection technology exhibits significant advantages in reducing attack risks and improving system robustness, effectively resisting various types of malicious attacks in complex network environments. Furthermore, this study innovatively applies federated learning to the security update mechanism of in-vehicle terminals, addressing the inefficiency and privacy leakage issues associated with traditional centralized update modes. Overall, this research provides theoretical support and technical references for the information security protection of intelligent connected vehicles, playing a crucial role in promoting industry standardization and practical application implementation.
Keywords：Intelligent Connected Vehicle; Information Security Protection; Encrypted Communication
目 录
摘要 I
Abstract II
一、绪论 1
(一) 智能网联汽车信息安全的研究背景 1
(二) 国内外研究现状与发展趋势 1
(三) 本文研究方法与技术路线 2
二、智能网联汽车信息安全威胁分析 2
(一) 网络攻击类型与特征 2
(二) 数据隐私泄露风险评估 3
(三) 车载系统漏洞分析 3
三、智能网联汽车信息安全防护技术 4
(一) 加密技术在车载通信中的应用 4
(二) 身份认证机制的设计与实现 5
(三) 入侵检测系统的构建与优化 5
四、智能网联汽车安全管理体系研究 6
(一) 安全策略的制定与实施 6
(二) 风险评估与应急响应机制 6
(三) 法规标准与行业规范探讨 7
结 论 9
参考文献 10
随着智能网联汽车的快速发展，其信息安全问题日益凸显，成为制约产业健康发展的关键因素。本研究旨在系统分析智能网联汽车面临的安全威胁，并提出针对性的信息安全防护技术方案。通过结合车联网架构特点与潜在攻击路径，研究设计了一种多层次、多维度的综合防护框架，涵盖数据加密传输、入侵检测与防御以及隐私保护等核心技术。具体而言，基于对称加密算法与非对称加密算法的优化组合，实现了高效且安全的数据通信；同时引入深度学习模型以增强入侵检测系统的实时性和准确性，并通过差分隐私技术保障用户敏感信息的安全性。实验结果表明，所提出的防护技术在降低攻击风险、提升系统鲁棒性方面具有显著优势，能够在复杂网络环境下有效抵御多种类型的恶意攻击。此外，该研究创新性地将联邦学习应用于车载终端的安全更新机制中，解决了传统集中式更新模式带来的效率低下和隐私泄露问题。总体而言，本研究为智能网联汽车的信息安全防护提供了理论支持和技术参考，对推动行业标准化建设及实际应用落地具有重要意义。
关键词：智能网联汽车；信息安全防护；加密通信
Abstract
With the rapid development of intelligent connected vehicles, their information security issues have become increasingly prominent, becoming a key factor constraining the healthy development of the industry. This study aims to systematically analyze the security threats faced by intelligent connected vehicles and propose targeted information security protection technical solutions. By integrating the characteristics of the vehicular network architecture with potential attack paths, a multi-layer and multi-dimensional comprehensive protection fr amework is designed, encompassing core technologies such as encrypted data transmission, intrusion detection and defense, as well as privacy protection. Specifically, an optimized combination of symmetric and asymmetric encryption algorithms is employed to achieve efficient and secure data communication. Meanwhile, deep learning models are introduced to enhance the real-time performance and accuracy of intrusion detection systems, and differential privacy technology is utilized to ensure the security of user-sensitive information. Experimental results demonstrate that the proposed protection technology exhibits significant advantages in reducing attack risks and improving system robustness, effectively resisting various types of malicious attacks in complex network environments. Furthermore, this study innovatively applies federated learning to the security update mechanism of in-vehicle terminals, addressing the inefficiency and privacy leakage issues associated with traditional centralized update modes. Overall, this research provides theoretical support and technical references for the information security protection of intelligent connected vehicles, playing a crucial role in promoting industry standardization and practical application implementation.
Keywords：Intelligent Connected Vehicle; Information Security Protection; Encrypted Communication
目 录
摘要 I
Abstract II
一、绪论 1
(一) 智能网联汽车信息安全的研究背景 1
(二) 国内外研究现状与发展趋势 1
(三) 本文研究方法与技术路线 2
二、智能网联汽车信息安全威胁分析 2
(一) 网络攻击类型与特征 2
(二) 数据隐私泄露风险评估 3
(三) 车载系统漏洞分析 3
三、智能网联汽车信息安全防护技术 4
(一) 加密技术在车载通信中的应用 4
(二) 身份认证机制的设计与实现 5
(三) 入侵检测系统的构建与优化 5
四、智能网联汽车安全管理体系研究 6
(一) 安全策略的制定与实施 6
(二) 风险评估与应急响应机制 6
(三) 法规标准与行业规范探讨 7
结 论 9
参考文献 10
