Abstract: The rapid, adaptive, and secure detection of network anomalies is critical in cybersecurity to prevent unauthorized access and malicious activities. The proposed framework integrates ...

Abstract: Out-of-distribution (OoD) inputs pose a persistent challenge to deep learning models, often triggering overconfident predictions on non-target objects. While prior work has primarily focused ...