AI Security and Privacy Protection: The Key to Building Trusted AI Systems

With the widespread application of AI technology, the issues of AI security and privacy protection are becoming increasingly prominent.

1、 Security threats faced by AI

  • adversarial attackDeceiving AI models through carefully constructed inputs
  • Data PoisoningInjecting malicious samples into training data
  • Model theftQuerying reverse engineering AI models through APIs
  • Prompt injectionManipulating the behavior of large models through malicious prompts

2、 Privacy protection technology

  1. Federated Learning: Data cannot be exported locally, model collaborative training
  2. Differential Privacy: Adding noise to data or models to protect individual privacy
  3. Secure multi-party computation: Multi party collaborative computation without leaking individual data

Enterprises should establish a comprehensive AI governance framework, including AI ethics committees, model audit mechanisms, data governance systems, and emergency response plans.