A review of recent advances, challenges, and opportunities in malicious insider threat detection using machine learning methods

FR Alzaabi, A Mehmood - IEEE Access, 2024 - ieeexplore.ieee.org
Insider threat detection has become a paramount concern in modern times where
organizations strive to safeguard their sensitive information and critical assets from …

Automation and orchestration of zero trust architecture: Potential solutions and challenges

Y Cao, SR Pokhrel, Y Zhu, R Doss, G Li - Machine Intelligence Research, 2024 - Springer
Zero trust architecture (ZTA) is a paradigm shift in how we protect data, stay connected and
access resources. ZTA is non-perimeter-based defence, which has been emerging as a …

User behaviour based insider threat detection using a hybrid learning approach

M Singh, BM Mehtre, S Sangeetha… - Journal of Ambient …, 2023 - Springer
Insider threats constitute a major cause of security breaches in organizations. They are the
employees/users of an organization, causing harm by performing any malicious activity …

Insider Threat Detection Model Using Anomaly-Based Isolation Forest Algorithm

T Al-Shehari, M Al-Razgan, T Alfakih… - IEEE …, 2023 - ieeexplore.ieee.org
Insider attacks may inflict far greater damage to an organization than outsider threats since
insiders are authorized users who are acquainted with the business's system, making …

User behavior analysis for detecting compromised user Accounts: A review paper

M Jurišić, I Tomičić, P Grd - Cybernetics and Information Technologies, 2023 - sciendo.com
The rise of online transactions has led to a corresponding increase in online criminal
activities. Account takeover attacks, in particular, are challenging to detect, and novel …

Machine learning approaches to detect, prevent and mitigate malicious insider threats: State-of-the-art review

A Jaiswal, P Dwivedi, RK Dewang - Multimedia Tools and Applications, 2024 - Springer
Insider threats are profoundly damaging and pose serious security challenges. These
threats, perpetrated by insiders, may arise from delinquency, retaliation, or motives such as …

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

W Yang, A Acuto, Y Zhou, D Wojtczak - arXiv preprint arXiv:2410.07612, 2024 - arxiv.org
Cyber-attacks are becoming increasingly sophisticated and frequent, highlighting the
importance of network intrusion detection systems. This paper explores the potential and …

Analytic-driven decision support in cybersecurity: towards effective IP risk management decision-making process

RS Dolas - 2023 - essay.utwente.nl
With the recent Covid-19 pandemic, the global work landscape has been altered forever.
More than 70% of the employees worked remotely. While this may be good news for …

TS-AUBD: A Novel Two-Stage Method for Abnormal User Behavior Detection

Y Cao, Y Chen, Y Wang, N Hu, Z Gu, Y Jia - Asia-Pacific Web (APWeb) …, 2024 - Springer
Malicious insider attacks are among the most destructive threats to enterprises. Solving the
insider threat problem involves several challenges, including data imbalance and detection …

Analysis of Malicious Insider Threats to Data Integrity

P Padiet - 2024 - researchoutput.csu.edu.au
The escalating concern regarding insider threats has emerged as a significant cybersecurity
challenge for various sectors, including organizations, financial institutions, and …