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: Subtly altering input data to trick a model into making incorrect predictions.
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 security
: Reconstructing sensitive training data from a model's predictions to compromise privacy. Deep Learning for Defense : Subtly altering input data to trick a
: Injecting malicious data into training sets to corrupt the learning process. security
Deep learning is increasingly used to build more robust security systems: Collection of Deep Learning Cyber Security Research Papers
Researchers focus on several critical vulnerabilities that can compromise AI models:

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