macOS Malware Analysis - Leveraging Data Science for Threat Detection

Dive into a 35-minute conference session from JNUC 2024 that unveils Jamf Threat Labs' cutting-edge approach to macOS malware detection through data science methodologies. Gain insights into the application of machine learning and visualization techniques for comprehensive malware sample analysis and semantic relationship identification. Explore Titan, an in-house tool developed by Jamf, and understand how it revolutionizes threat classification by revealing intricate similarities between malware binaries. Master advanced threat analysis techniques that combine data science principles with cybersecurity practices to enhance malware detection capabilities on macOS systems.