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cs.CR2025
HYDRA: A Hybrid Heuristic-Guided Deep Representation Architecture for Predicting Latent Zero-Day Vulnerabilities in Patched Functions
Mohammad Farhad, Sabbir Rahman, Shuvalaxmi Dass
Software security testing, particularly when enhanced with deep learning models, has become a powerful approach for improving software quality, enabling faster detection of known f…
cs.SE2025
Evolutionary Defense: Advancing Moving Target Strategies with Bio-Inspired Reinforcement Learning to Secure Misconfigured Software Applications
Niloofar Heidarikohol, Shuvalaxmi Dass, Akbar Siami Namin
Improper configurations in software systems often create vulnerabilities, leaving them open to exploitation. Static architectures exacerbate this issue by allowing misconfiguration…