A Recursive Neural Network (RNN) is a type of artificial neural network designed to process sequential data by maintaining a form of memory. Unlike traditional neural networks, RNNs have connections that loop backward, allowing information from previous steps in a sequence to influence the current output. This makes them effective for tasks where context or order matters, such as language modeling, speech recognition, and anomaly detection in cybersecurity. In cybersecurity, RNNs can analyze sequences of network traffic or user actions to detect suspicious patterns or intrusions, leveraging their ability to remember and relate past events to current observations.