Counter Denial of Service for Next-Generation Networks within the Artificial Intelligence and Post-Quantum Era

TL;DR

This paper explores advanced counter-DoS strategies for next-generation networks, emphasizing AI and post-quantum security, and proposes integrated, collaborative, and proactive defense mechanisms to enhance system resilience.

Contribution

It provides a comprehensive analysis of DoS threats in the AI and post-quantum era, highlighting gaps and proposing synergistic, AI-driven, and quantum-aware countermeasures.

Findings

AI-based intrusion detection improves early DoS attack identification

Federated learning enhances collaborative DoS defense

Proactive schemes like honeypots and puzzles strengthen prevention

Abstract

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.