Deep Learning for Realtime Malware Detection

Deep Learning for Realtime Malware Detection

Explore a comprehensive conference talk on using deep learning for real-time malware detection, focusing on Domain Generation Algorithm (DGA) malware. Learn about an ensemble model combining convolutional neural networks, long short-term memory networks, and natural language processing to analyze domains and identify potentially malicious machine-generated addresses. Discover how these deep learning models, built with Keras and TensorFlow, can capture complex patterns without manual feature engineering and resist reverse engineering attempts. Gain insights into the system's ability to process enterprise-scale network traffic in real-time, make predictions, and alert cybersecurity analysts. Understand the speakers' backgrounds in data engineering, computer science, and cybersecurity, and explore the talk's detailed syllabus covering various aspects of malware detection, deep learning architectures, and practical applications in cybersecurity.