车辆互联网 (IoV) 的安全和信任管理:挑战和机器学习解决方案
1College of Computer Science and Engineering, Taibah University, Yanbu 46421, Saudi Arabia.
Sensors (Basel, Switzerland)
|January 23, 2024
概括
汽车互联网 (IoV) 面临着安全和信任方面的挑战. 机器学习 (ML) 为增强 IoV 安全性和信任管理系统提供了一个有前途的解决方案.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 网络工程 网络工程
背景情况:
- 车辆互联网 (IoV) 是物联网 (IoT) 的扩展,使车辆与所有东西之间的通信成为可能.
- IoV旨在改善驾驶,能源效率,数据安全和道路安全.
- 安全和信任管理是 IoV 环境中的关键挑战.
研究的目的:
- 提供对IoV和信任管理的概述.
- 讨论IOV的安全要求,挑战和攻击.
- 探索机器学习 (ML) 在解决 IoV 安全和信任问题的潜力.
主要方法:
- 查看有关 IoV 安全性和信任管理的现有文献.
- 机器学习技术的分类适用于 IoV.
- 审查基于机器学习的IoV安全和信任管理方案.
主要成果:
- 在 IoV 环境中确定了关键的安全和信任挑战.
- 分类了与IoV安全相关的各种ML技术.
- 强调了ML在提高IoV安全性和信任方面的有效性.
结论:
- 机器学习为克服IoV安全和信任挑战提供了一种强大的方法.
- 基于机器学习的解决方案对于未来开发安全可靠的IoV系统至关重要.
- 这项调查为了解和推进 IoV 安全中的 ML 应用提供了基础.
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