Electric and Flying Vehicles (EnFVs) represent a transformative shift in transportation, promising enhanced efficiency and reduced environmental impact. However, their integration into interconnected digital ecosystems poses significant cybersecurity challenges, including cyber-physical threats, privacy vulnerabilities, and supply chain risks. This paper comprehensively explores these challenges and investigates artificial intelligence (AI)-driven solutions to bolster EnFV cybersecurity. The study begins with an overview of EnFV cybersecurity issues, emphasizing the increasing complexity of threats in digital transportation systems. Methodologically, the paper reviews existing literature to identify gaps and assesses recent advancements in AI for cybersecurity applications. Key methodologies include AI-powered intrusion detection, threat analysis leveraging machine learning algorithms, predictive maintenance strategies, and enhanced authentication protocols. Results underscore the effectiveness of AI technologies in mitigating EnFV cybersecurity risks, demonstrating improved threat detection and response capabilities. The study concludes by outlining future research directions, highlighting the need for continued innovation in AI, quantum computing resilience, blockchain applications, and ethical considerations. These findings contribute to a clearer understanding of EnFV cybersecurity dynamics and provide a roadmap for enhancing the security and reliability of future transportation systems.

中文翻译：

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电动和飞行车辆的网络安全：威胁、挑战、人工智能解决方案和未来方向


电动和飞行车辆 （EnFV） 代表了交通的变革性转变，有望提高效率并减少对环境的影响。然而，它们与互联数字生态系统的集成带来了重大的网络安全挑战，包括网络物理威胁、隐私漏洞和供应链风险。本白皮书全面探讨了这些挑战，并研究了人工智能 （AI） 驱动的解决方案，以加强 EnFV 网络安全。该研究首先概述了 EnFV 网络安全问题，强调了数字交通系统中威胁的日益复杂。在方法上，本文回顾了现有文献以确定差距并评估了人工智能在网络安全应用中的最新进展。主要方法包括 AI 驱动的入侵检测、利用机器学习算法的威胁分析、预测性维护策略和增强的身份验证协议。结果强调了 AI 技术在降低 EnFV 网络安全风险方面的有效性，展示了改进的威胁检测和响应能力。该研究最后概述了未来的研究方向，强调了在 AI、量子计算弹性、区块链应用和道德考虑方面持续创新的必要性。这些发现有助于更清楚地了解 EnFV 网络安全动态，并为提高未来交通系统的安全性和可靠性提供路线图。