DeepStage uses AI to learn autonomous defense against multi-stage cyberattacks

Researchers have developed DeepStage, a new framework utilizing deep reinforcement learning to create autonomous defense policies against multi-stage cyberattacks. The system models enterprise environments as partially observable Markov decision processes, fusing host and network data into provenance graphs. DeepStage employs a graph neural network and LSTM to estimate attacker stages, guiding a hierarchical agent to select optimal defense actions for monitoring, containment, and remediation. AI

影响 This framework could enhance autonomous defense capabilities against sophisticated, multi-stage cyber threats.

排序理由 This is a research paper detailing a new framework for cybersecurity defense. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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