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.
Beispiel
An attacker tries to force a corporate chatbot to disclose an internal document through a specially formulated request.
Warum es wichtig ist
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.
So funktioniert es
The system is protected through authentication, authorization, encryption, context restrictions, filters, attack tests, monitoring of suspicious requests and separation of rights.
Wo es genutzt wird
- chatbot protection
- API security
- corporate assistants
Einschränkungen
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.
FAQ
Why is “AI Security” useful to know?
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.