Security and Privacy in Machine Learning

Machine learning technologies have the potential to transform and revolutionize various industries, such as drug discovery by finding new molecules, medical diagnosis by analyzing images and signals, fraud prevention by detecting anomalies, and security by recognizing faces and objects. However, training and utilizing machine learning models requires handling large volumes of sensitive and private data. In this article, we discuss some of the security and privacy challenges in this process. We focus mainly on how we can securely compute machine learning algorithms over sensitive data, but we also describe data privacy problems in this domain and how we can mitigate them.