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Reinforcement Learning for Autonomous Defence in Software-Defined Networking
[article]
2018
arXiv
pre-print
Despite the successful application of machine learning (ML) in a wide range of domains, adaptability---the very property that makes machine learning desirable---can be exploited by adversaries to contaminate training and evade classification. In this paper, we investigate the feasibility of applying a specific class of machine learning algorithms, namely, reinforcement learning (RL) algorithms, for autonomous cyber defence in software-defined networking (SDN). In particular, we focus on how an
arXiv:1808.05770v1
fatcat:wiocs64zi5aezazzi4ko7rh43y