DON’T TRUST THE ROBOTS. THEY ARE NOT SECURE.
In order to shed light on the world of adversarial machine learning, CalypsoAI staff member Ilja Moisejevs has prepared a series articles on Towards Data Science to inform readers as to the cutting art of the science and the risks it brings.
What Everyone Forgets about Machine Learning – Provides an overview of machine learning security threats and the parallels of these threats to traditional cybersecurity.
Will my Machine Learning System be Attacked – Here, CalypsoAI details our threat model for machine learning systems and provides a blueprint for understanding attacks.
Poisoning Attacks on Machine Learning – This is a primer on poisoning attacks to machine learning, including information on how an attacker can poison a data lake to install a backdoor.
Evasion attacks on Machine Learning (or “Adversarial Examples”) – The most common form of attack on machine learning systems, evasion attacks are something all machine learning users must be aware of and defended against.
Privacy Attacks on Machine Learning – Models and data can be stolen. Here CalypsoAI discusses the state of the art.
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