Insider threat prediction using deep learning is a growing area of research that focuses on the use of machine learning techniques to identify potential insider threats within an organization. Insider threats refer to individuals who have access to an organization’s resources and systems, but who may pose a risk to the security or integrity of those systems. Deep learning techniques, such as artificial neural networks, can be used to analyze large amounts of data and identify patterns or behaviors that may indicate a potential insider threat. These techniques can be particularly effective at detecting subtle, nuanced patterns that may be difficult for humans to identify. By using deep learning to predict insider threats, organizations can take proactive measures to protect their systems and data from potential threats.