System and method for preventing introduction of poisoned training data to artificial intelligence models

Abstract

Methods and systems for managing artificial intelligence (AI) models are disclosed. To manage AI models, an instance of an AI model may not be re-trained using training data determined to be too similar to previously used training data. By doing so, malicious attacks intending to shift the AI model in a particular direction using poisoned training data may be prevented. To do so, a candidate training data set may be analyzed prior to performing re-training of an instance of an AI model using the candidate training data set. The analysis may result in a score. If the score exceeds a score threshold, the candidate training data set may be considered to contain poisoned training data. If the score does not exceed the score threshold, the candidate training data set may be accepted as usable to train an instance of the AI model.