arXiv:2503.17867v3 Announce Type: replace-cross Abstract: Distributed Denial of Service attacks represent an active cybersecurity research problem. Recent research shifted from static rule-based defenses towards AI-based detection and mitigation. This comprehensive survey covers several key topics. Preeminently, state-of-the-art AI detection methods are discussed. An in-depth taxonomy based on manual expert hierarchies and an AI-generated dendrogram are provided, thus settling DDoS categorization ambiguities. An important discussion on available datasets follows, covering data format options a
The increasing sophistication and frequency of DDoS attacks continue to drive the need for more advanced and adaptive defense mechanisms, making AI a central solution.
This survey highlights how AI is becoming indispensable for cybersecurity, particularly in defending against distributed denial of service attacks, which can cripple digital infrastructure.
The shift from static rule-based DDoS defenses to dynamic AI-based detection and mitigation strategies is accelerating, standardizing the approach across the cybersecurity landscape.
- · Cybersecurity AI solution providers
- · Organizations with critical online infrastructure
- · AI researchers in cybersecurity
- · Traditional rule-based cybersecurity vendors
- · Attackers relying on common DDoS tactics
Widespread adoption of AI for DDoS defense will improve network resilience and reduce attack effectiveness.
This will likely lead to an 'AI arms race' where attackers also leverage AI to bypass defenses, creating more complex cyber threats.
The escalating complexity could necessitate global AI-driven cybersecurity alliances and shared threat intelligence platforms to maintain digital stability.
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Read at arXiv cs.AI