GAT-APG: Graph Attention Network-Based Attack Path Generation for Security Simulation

GAT-APG: Graph Attention Network-Based Attack Path Generation for Security Simulation

Existing attack path generation methods face limitations in dynamic simulation environments due to their reliance on static network models and computational inefficiencies when network configurations change frequently. This study proposes GAT-APG, a reinforcement learning framework that combines Gra...

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Bibliographic Details
Main Authors: Min Geun Song, Jaewoong Choi, Huy Kang Kim
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Cyber attack simulation
graph neural network
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/11131165/
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https://ieeexplore.ieee.org/document/11131165/

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