Explore the evolution of adversarial AI in this 30-minute conference talk from the Hack In The Box Security Conference. Delve into the history of AI security from 2004 to the present, examining how the threat landscape has shifted towards AI-driven technologies. Learn about vulnerabilities in self-driving cars, facial recognition systems, drones, voice assistants, and financial algorithms. Gain insights from nearly 2000 research papers on insecure and malicious AI, presented by Alex Polyakov, a trusted AI and cybersecurity expert. Discover the progression of cyber security through different technological eras, understand the top 10 AI attacks, and explore defense strategies and frameworks for protecting AI systems. Equip yourself with knowledge on the challenges and future implications of AI security in this comprehensive overview of adversarial machine learning.
Overview
Syllabus
Introduction
Agenda
History of Cyber Security
Adversarial Machine Learning
Countries Contribution
Progress
AI Attacks
Data
Top 10 Attacks
Evasion Attack
Facial Recognition
Challenges
Framework
Protection
Defense
Life Cycle
Conclusion
Taught by
Hack In The Box Security Conference
Related Courses
-
Practical AI Red Teaming - A Facial Recognition Case Study
-
Trusted and Responsible AI - Explainability, Adversarial Attacks, Bias, and Fairness
-
Defending Against Adversarial Model Attacks Using Kubeflow
-
AI Security Engineering - Modeling - Detecting - Mitigating New Vulnerabilities
-
Model Robustness Will Hurt Data Privacy?
-
Fighting New Era Bandits Who Are Plundering Your AI - ML Application
