What is AI Security
Protecting AI systems from attacks, leaks, abuse, unauthorized access and dangerous behavior.
Definition
The security of AI systems is closer to cybersecurity and infrastructure protection. It includes access control, API protection, input validation, hint injection protection, monitoring, logging, and secrets management. Unlike general AI security, there is a greater focus on technical threats.
Example
An attacker tries to force a corporate chatbot to disclose an internal document through a specially formulated request.
Why it matters
The term is important for developers and service owners: AI is often connected to data and tools, so it needs to be protected as a full-fledged part of the infrastructure.
How it works
The system is protected through authentication, authorization, encryption, context restrictions, filters, attack tests, monitoring of suspicious requests and separation of rights.
Where it is used
- chatbot protection
- API security
- corporate assistants
Limitations
AI systems are creating new attack surfaces. Conventional application protection is necessary, but it is not enough without checking specific attacks on models and hints.