Adversarial Testing
Deliberate, structured testing that simulates malicious or unexpected inputs to find vulnerabilities or failure modes in an AI system.
Definition
A form of robustness testing that evaluates system behaviour under malicious, manipulated, or adversarial inputs and attack vectors to identify vulnerabilities such as model evasion, data poisoning or manipulation, and to inform mitigation measures.
Related Terms
Red Teaming
A structured, adversarial testing process that simulates intentional misuse to find vulnerabilities, failure modes, and harms in AI systems before deployment....
Robustness
The ability of an AI system to maintain acceptable performance and resist failures, attacks, or unexpected conditions across its lifecycle....
Model evaluation
Technical assessment processes for AI models (benchmarks, red‑teaming)....
Post-Market Monitoring
Ongoing surveillance of AI system performance after deployment in the market....