Beyond Human Detection: Advanced AI-based Intrusion Detection Model for Detecting Insider Threats in Cybersecurity
Code for detecting insider threats using a deep learning model applied to tabular data. Deep feature synthesis is employed to construct detailed tabular user profiles based on event data. Then, a binary deep learning model is developed to achieve three objectives: (i) identification of malicious users through supervised learning, (ii) evaluation of how well generative algorithms can mimic real user profiles, and (iii) differentiation between real and synthetic abnormal activities.
This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree.
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