Explore the world of hacking machine learning systems in this conference talk from 44CON 2018. Delve into the emerging field of Adversarial ML, learning how to exploit weak points in speech, text, and face recognition algorithms. Discover techniques for achieving unexpected consequences, data leakage, memory corruption, and output manipulation in ML systems. Witness a live demonstration showcasing the potential vulnerabilities in these intelligent systems. Gain insights into the top 5 attacks based on CVSS and business impact, and understand where to focus your offensive research. Learn about various attack methods, including cloning, backdoors, encoding, and adversarial attacks on audio and visual recognition systems. Examine real-world examples, such as misclassifying rifles as bananas and evading next-generation antivirus software using AI. Equip yourself with knowledge to better understand and address the security challenges posed by machine learning technologies.
JARVIS Never Saw It Coming - Hacking Machine Learning in Speech, Text and Face Recognition