What is Backdoor Attack in Applied AI?
A poisoning attack that installs a trigger phrase, pattern, or input perturbation that activates an attacker-chosen behavior. The model behaves normally on clean inputs and reveals the backdoor only when the trigger appears. Detection is hard because the model's accuracy on standard benchmarks is unaffected.
Why Backdoor Attack Matters for Your AI or Cybersecurity Career
Supply-chain risk for open-weight models depends on detecting backdoors. AI security engineering teams design scanners and rebuild-from-source policies around this risk.
Related Applied AI Terms
A poisoning attack that installs a trigger phrase, pattern, or input perturbation that activates an attacker-chosen behavior. The model behaves normally on clean inputs and reveals the backdoor only when the trigger appears. Detection is hard because the model's accuracy on standard benchmarks is unaffected.
Supply-chain risk for open-weight models depends on detecting backdoors. AI security engineering teams design scanners and rebuild-from-source policies around this risk.
Definitions are original explanations written for career development purposes. For authoritative technical definitions, refer to NIST, ISO, or the relevant standards body.
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