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Machine learning models are increasingly prevalent across industries but have become vulnerable to various attacks. So, what can organizations do to better protect themselves?
This article gives into key threats, including model theft, modification, attacks on ML applications, and adversary leapfrogging of the training process. Additionally, it covers the best ways to address these risks, highlighting recommendations such as a multi-faceted approach combining robust licensing, encryption, and software protection tools.
Browse the article to gain more insight and discover how to safeguard your investments and maintain a competitive edge in the era of AI and ML.