Safeguarding Machine Learning Systems - A Comprehensive Security Plan

Explore a comprehensive security framework for machine learning systems in this 51-minute conference talk from LASCON. Delve into major security risks like adversarial attacks and data poisoning before learning practical defensive strategies across five key domains. Master data security principles including encryption, access control, and anonymization techniques. Discover model security approaches such as watermarking and adversarial robustness training. Learn platform security best practices for configuration and monitoring. Understand how to implement security compliance measures that promote ethical AI deployment through transparency and accountability. Gain essential knowledge about human security elements including staff training protocols. Walk away with actionable insights for implementing security measures throughout the machine learning lifecycle to create more resilient and trustworthy AI systems.