김정윤, 박종열, 오상호,

Vol. 34, No. 1, pp. 21-29, 2월. 2024
https://doi.org/10.13089/JKIISC.2024.34.1.21, Full Text:
Keywords: Reinforcement Learning, information security, Network, DQN
Abstract

With the development of ICT and network, security management of IT infrastructure that has grown in size is becoming very difficult. Many companies and public institutions are having difficulty managing system and network security. In addition, as the complexity of hardware and software grows, it is becoming almost impossible for a person to manage all security. Therefore, AI is essential for network security management. However, since it is very dangerous to operate an attack model in a real network environment, cybersecurity emulation research was conducted through reinforcement learning by implementing a real-life network environment. To this end, this study applied reinforcement learning to the network environment, and as the learning progressed, the agent accurately identified the vulnerability of the network. When a network vulnerability is detected through AI, automated customized response becomes possible.

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