Advanced Insider Threat Detection: Integrating LSTM and Random Forest for User Behavior Analysis

Traditional security measures often fall short in detecting malicious insiders. This book introduces an innovative insider threat detection model leveraging the power of deep learning and ensemble methods. By capturing temporal dependencies in user behavior through LSTM networks and employing the robust classification capabilities of Random Forest, this research offers a significant step forward in safeguarding sensitive information from internal threats.