Given the rise in cyber threats to networked systems, coupled with the proliferation of AI techniques and enhanced processing capabilities, Denial of Service (DoS) attacks are becoming increasingly sophisticated and easily executable. They target system availability, compromising entire systems without breaking underlying security protocols. Consequently, numerous studies have focused on preventing, detecting, and mitigating DoS attacks. However, state-of-the-art systematization efforts have limitations such as isolated DoS countermeasures, shortcomings of AI-based studies, and a lack of DoS integration features like privacy, anonymity, authentication, and transparency. Additionally, the emergence of quantum computers is a game changer for DoS from attack and defense perspectives, yet it has remained largely unexplored. This study aims to address these gaps by examining (counter)-DoS in the AI era while also considering post-quantum (PQ) security when it applies. We highlight the deficiencies in the current literature and provide insights into synergistic techniques to bridge these gaps. We explore AI mechanisms for DoS intrusion detection, evaluate cybersecurity properties in cutting-edge machine learning models, and analyze weaponized AI in the context of DoS. We also investigate collaborative and distributed counter-DoS frameworks via federated learning and blockchains. Finally, we assess proactive approaches such as honeypots, puzzles, and authentication schemes that can be integrated into next-generation network systems for DoS prevention and mitigation.

翻译：鉴于网络系统面临的网络威胁日益增多，加之人工智能技术的普及和处理能力的提升，拒绝服务（DoS）攻击正变得越来越复杂且易于实施。此类攻击以系统可用性为目标，在不破坏底层安全协议的情况下危及整个系统。因此，大量研究聚焦于预防、检测和缓解DoS攻击。然而，现有最先进的系统化研究存在诸多局限，例如孤立的DoS防御措施、基于AI研究的不足，以及缺乏隐私性、匿名性、认证和透明性等DoS集成特性。此外，量子计算机的出现从攻击和防御角度彻底改变了DoS的格局，但这一领域在很大程度上仍未得到充分探索。本研究旨在通过审视AI时代的（对抗）DoS问题，并在适用时考虑后量子（PQ）安全性，以填补这些空白。我们指出了当前文献中的不足，并提出了协同技术以弥合这些差距的见解。我们探讨了用于DoS入侵检测的AI机制，评估了前沿机器学习模型中的网络安全属性，并分析了DoS背景下武器化AI的应用。我们还通过联邦学习和区块链技术研究了协作式分布式抗DoS框架。最后，我们评估了可集成到下一代网络系统中用于DoS预防和缓解的主动防御方法，如蜜罐、验证谜题和认证方案。