Security May 2026

: Injecting malicious data into training sets to corrupt the learning process.

: Reverse-engineering a trained model to reveal its parameters or architecture. security

The intersection of security and deep learning covers two primary areas: using deep learning to security (e.g., intrusion detection) and protecting deep learning models from vulnerabilities (e.g., adversarial attacks) . Key Security Threats to Deep Learning : Injecting malicious data into training sets to

Researchers focus on several critical vulnerabilities that can compromise AI models: security

: Subtly altering input data to trick a model into making incorrect predictions.