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Adversarial Machine Learning: A Beginner’s Guide to Adversarial Attacks and Defensesby@miguelhzbz
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2,750 reads

Adversarial Machine Learning: A Beginner’s Guide to Adversarial Attacks and Defenses

by Miguel Hernández5mJanuary 9th, 2022
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There are [four types of attacks] that ML models can suffer. An adversary steals a copy of a remotely deployed machine learning model, given oracle prediction access. Extraction attacks aim to extract as much information as possible and with the set of inputs and outputs train a model called substitute model. Extract model is hard**, the attacker needs a huge compute capacity to re-training the new model with accuracy and fidelity, and substitute model is equivalen to training a model from the ground up.

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Miguel Hernández

Miguel Hernández

@miguelhzbz

Security researcher that learns and manifests new concepts and skills continuously. Speaker at several sec conferences.

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Miguel Hernández@miguelhzbz
Security researcher that learns and manifests new concepts and skills continuously. Speaker at several sec conferences.

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