Adversarial Machine Learning

Adversarial machine learning is a field of study in Artificial Intelligence that focuses on misleading or fooling systems by providing incorrect data deliberately. In such cases, the data is slightly deviated from facts and fed to the system eventually causing the AI to make errors. These changes are made to deceive the AI system to misinterpret the data. The changes could lead the AI to mistake one object for another, etc. Studying adversarial machine learning not only helps to understand how AI can be deceived but also to develop systems that are resistant to such attacks. It helps in developing systems that are robust, secure, and trustworthy which is essential in autonomous vehicles, security systems, and more.