Before revision:  In this work, we present different types of insider trading approaches, techniques and our proposed approach for detecting and predicting insider trader using a deep-learning based approach combined with discrete signal processing on  time series data  .
After revision:  In this work, we present different types of insider trading approaches, techniques and our proposed approach for detecting and predicting insider trader using a deep-learning based approach combined with discrete signal processing on time series data . In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns .