Security and Privacy in AI
Audience: Product Leads, Engineering Management, Executives
Resource Summary: Are you building AI capabilities into your product? Security and privacy are paramount. Learn about key topics in privacy, data protection, and how to build trustworthy systems for your customers.
Key Topics: Securing data for AI, managing data sources, balancing data utility and privacy in model training, data re-identification, data integrity, provenance, compliance considerations, and the shared responsibility model
Model Security and GenAI Attack Threats
Audience: Engineering Staff, Developers, Security Engineers, CIO / CTO / CISO, Technical Product Managers
Resource Summary: Learn how to protect AI models from adversarial attacks and maintain their integrity through robust design and defense mechanisms. Gain an understanding of common GenAI attack threats and how to mitigate them.
Key Topics: Model security, data integrity, prompt hacking such as prompt injection and jailbreaking, adversarial attacks including backdoor and data poisoning attacks, gradient leakage, membership inference attacks, instruction defense tactics, differential privacy topics, general defense methods
AI System Security and Infrastructure
Audience: DevOps, Developers, Infrastructure Management, CIO / CISO
Resource Summary: Protect the integrity and security of AI systems’ underlying infrastructure, including hardware, software, cloud, and APIs.
Key Topics: LLM hardware requirements, sandboxing, edge security, API security, access controls, third-party considerations, secure hosting, data management, network security, SIEM and monitoring
Cryptographic Techniques for AI Security and Privacy
Audience: Developers, Security Engineers, CTO / CISO
Resource Summary: Fundamental to AI models is data, and lots of it. Learn how cryptographic methods can be used to protect the integrity of AI training and model generation, manage data sources, address data loss prevention, and implement data security.
Key Topics: Applied cryptography, tokenization, AES encryption, RSA encryption, key management, key rotation, hardware security modules, secrets management, DevOps and model development pipelines, data security, data loss prevension
Advanced Techniques for Defending Against Prompt Injection and Jailbreaking Attacks
AI Resources > Security and Privacy Overview > Advanced Techniques for Defending Against Prompt Injection…
Addressing Regulatory Compliance as a Catalyst for Secure AI Data Handling
AI Resources > Security and Privacy Overview > Addressing Regulatory Compliance as a Catalyst for…
Protecting AI Systems from Data Poisoning Attacks
AI Resources > Security and Privacy Overview > Protecting AI Systems from Data Poisoning Attacks…
The Broken Chain: Why Data Provenance Is the Missing Link in AI Risk Management
AI Resources > Security and Privacy Overview > The Broken Chain: Why Data Provenance Is…