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통찰 - Artificial Intelligence Cybersecurity
Optimizing Lightweight Malware Detection Models for Resource-Constrained AIoT Devices
This research aims to optimize a robust meta-learning ensemble model for malware detection on resource-constrained AIoT devices by reducing model size and inference duration while maintaining high accuracy and low false positive rates.
Approximate Bayesian Computation: A Novel Approach to Informed Fuzzing and Vulnerability Detection
Approximate Bayesian Computation (ABC) represents a probabilistic approach to address the challenges of comprehensive fuzz testing, which is computationally expensive and practically impossible given the infinite possible input sequences.
