## 4 Dataset
### Data Acquisition
(2015) [PERSON]; [PERSON]; [PERSON]; [PERSON] Caught in the act of an insider attack: Detection and assessment of insider threat. In Proceedings of the 2015 IEEE International Symposium on Technologies for Homeland Security (HST), Waltham, MA, USA, 14-16 April 2015; pp. 1-6. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON] Automated Insider Threat Detection System Using User and Role-Based Profile Assessment. _IEEE Syst. J._**2017**, _11_, 503-512. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON] Insider Threat Modeling: An Adversarial Risk Analysis Approach. _IEEE Trans. Inf. Forensics Secur._**2021**, _16_, 1131-1142. [CrossRef]
* [PERSON] et al. (2021) [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] An adversarial risk analysis framework for cybersecurity. _Risk Anal._**2021**, _41_, 16-36. [CrossRef]
* [PERSON] (2021) [PERSON] A systematic approach to develop an advanced insider attacks detection module. _J. Eng. Appl. Sci._**2021**, \(8\), 33. [CrossRef]
* [PERSON] (2021) [PERSON]; [PERSON] A Fine-Grained Approach for Anomaly Detection in File System Accesses With Enhanced Temporal User Profiles. _IEEE Trans. Dependable Secur. Comput._**2021**, _18_, 2535-2550. [CrossRef]
* [PERSON] and [PERSON] (2022) [PERSON]; [PERSON]; [PERSON] Abnormality Detection in Network Traffic by Classification and Graph Data Analysis. In Proceedings of the 2022 IEEE 13 th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 12-15 October 2022; pp. 0041-0047. [CrossRef]
* [PERSON] and [PERSON] (2022) [PERSON]; [PERSON] Preventing Data Breaches: Utilizing Log Analysis and Machine Learning for Insider Attack Detection. In Proceedings of the 2022 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA, 14-16 December 2022; pp. 1022-1027. [CrossRef]
* [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON]; [PERSON] Deep and machine learning approaches for anomaly-based intrusion detection of imbalanced network traffic. _IEEE Sens. Lett._**2018**, \(3\), 7101404. [CrossRef]* [PERSON] (2018) [PERSON]; [PERSON] Evaluating insider threat detection workflow using supervised and unsupervised learning. In Proceedings of the 2018 IEEE Security and Privacy Workshops (SPW), San Francisco, CA, USA, 24 May 2018; pp. 270-275. * [PERSON] et al. (2023) [PERSON]; [PERSON]; [PERSON]; [PERSON] BGP Dataset-Based Malicious User Activity Detection Using Machine Learning. _Information_**2023**, 14, 501. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON] Intrusion detection model for imbalanced dataset using SMOTE and random forest algorithm. In Advances in Cyber Security Proceedings of the Third International Conference, ACes 2021, Penang, Malaysia, 24-25 August 2021; Revised Selected Papers 3; Springer: Berlin/Heidelberg, Germany, 2021; pp. 361-378. * [PERSON] et al. (2002) [PERSON]; [PERSON]; [PERSON] [PERSON] A framework to detect the malicious insider threat in cloud environment using supervised learning methods. In Proceedings of the 2022 9 th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 23-25 March 2022; pp. 354-358. * [PERSON] (2021) [PERSON]; [PERSON] Anomaly Detection for Insider Threats Using Unsupervised Ensembles. _IEEE Trans. Netw. Serv. Manag._**2021**, 18, 1152-1164. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON] Super Learner Ensemble for Anomaly Detection and Cyber-Risk Quantification in Industrial Control Systems. _IEEE Internet Things J._**2022**, _9,_ 13279-13297. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON] Design of an ensemble learning behavior anomaly detection framework. _Int. J. Comput. Inf. Eng._**2019**, _13_, 547-555. * [PERSON] and [PERSON] (2024) [PERSON]; [PERSON] Insider Threat Detection Model Enhancement Using Hybrid Algorithms between Unsupervised and Supervised Learning. _Electronics_**2024**, _13_, 973.