Intelligent Prevention of DDoS Attacks using Reinforcement Learning and Smart Contracts
DOI:
https://doi.org/10.32473/flairs.37.1.135349Palavras-chave:
Reinforcement Learning, smart contracts, CybersecurityResumo
(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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Copyright (c) 2024 Emily Struble, Maikel Leon Espinosa, Erotokritos Skordilis
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Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial 4.0 International License.