Tags → #dynamic analysis

Research Proposes Fuzzing Techniques for Machine Learning Security

Recent research highlights vulnerabilities in machine learning frameworks and proposes methodologies, including dynamic analysis and fuzzing, to enhance their security and reliability.
SLIFER Architecture Enhances Malware Detection Performance and Robustness

Recent research on the SLIFER architecture has demonstrated significant improvements in malware detection accuracy and robustness against adversarial attacks, emphasizing the importance of model calibration and innovative methodologies in cybersecurity.
Study Develops LLM-Based Method for Malware Detection

A recent study from Pennsylvania State University introduces a Large Language Model-based workflow aimed at identifying anti-dynamic analysis techniques used by malware to evade detection in sandbox environments.