Intelligent Prevention of DDoS Attacks using Reinforcement Learning and Smart Contracts

Authors

Keywords:

Reinforcement Learning, smart contracts, Cybersecurity

Abstract

(Distributed) Denial-of-Service (DoS/DDoS) attacks are among the most dangerous cybersecurity threats to computer networks. Lately, blockchain and artificial intelligence (AI) cyberdefense applications have successfully been implemented to identify attack patterns. This paper proposes a novel collaborative, blockchain-based multi-agent reinforcement learning (RL) cyberdefense method using smart contracts. Initial numerical experiments have shown that the agents quickly learn to predict attacks, which can lead to mitigating network-wide service disruptions.

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Published

13-05-2024

How to Cite

Emily Struble, Leon Espinosa, M., & Skordilis, E. (2024). Intelligent Prevention of DDoS Attacks using Reinforcement Learning and Smart Contracts. The International FLAIRS Conference Proceedings, 37(1). Retrieved from https://journals.flvc.org/FLAIRS/article/view/135349