Deep Adversarial Architectures for Detecting and Generating Maliciousness

This course covers deep adversarial architectures for detecting and generating maliciousness. The learning outcomes include understanding deep learning packages, deep learning models, vulnerabilities in deep learning, and the application of deep learning in security. The course teaches skills such as using autoencoders, distinguishing between red team and blue team approaches, and conducting vulnerability assessments. The teaching method involves a lecture format with topics ranging from shallow learning to deep adversarial architectures. The intended audience for this course is individuals interested in cybersecurity, machine learning, and deep learning applications in security.