What is Adversarial Machine Learning? - KDnuggets

With the continuous rise in Machine Learning (ML), our society becomes heavily reliant on its applications in the real world. However the more dependent we become on Machine Learning models, the more vulnerabilities on how to defeat these models. The dictionary definition of an "adversary" is: "one that contends with, opposes, or resists" In the Cybersecurity sector, adversarial machine learning attempts to deceive and trick models by creating unique deceptive inputs, to confuse the model resulting in a malfunction in the model. Adversaries may input data that have an intention to compromise or alter the output and exploit its vulnerabilities. We are unable to identify these inputs through the human eye, however, it causes the model to fail.