[HTML][HTML] A review of insider threat detection: Classification, machine learning techniques, datasets, open challenges, and recommendations
Insider threat has become a widely accepted issue and one of the major challenges in
cybersecurity. This phenomenon indicates that threats require special detection systems …
cybersecurity. This phenomenon indicates that threats require special detection systems …
[HTML][HTML] Insider threat detection in cyber-physical systems: a systematic literature review
The rapid expansion of cyber-physical systems (CPSs) has introduced new security
challenges, leading to the emergence of various threats, attacks, and controls aimed at …
challenges, leading to the emergence of various threats, attacks, and controls aimed at …
[PDF][PDF] An integrated imbalanced learning and deep neural network model for insider threat detection
The insider threat is a vital security problem concern in both the private and public sectors. A
lot of approaches available for detecting and mitigating insider threats. However, the …
lot of approaches available for detecting and mitigating insider threats. However, the …
Mitigating insider threat: a neural network approach for enhanced security
Detecting insider threats is the foremost challenge in many institutions because of the
abnormal behavior of legitimate access and network crawling in the Internet of Things (IoT) …
abnormal behavior of legitimate access and network crawling in the Internet of Things (IoT) …
Home based monitoring for smart health‐care systems: a survey
Internet of Things (IoT) is one of the greatest advancements in technology especially in the
medical field. The interconnection of medical devices with the internet makes it easier to …
medical field. The interconnection of medical devices with the internet makes it easier to …
GMFITD: Graph Meta-Learning for Effective Few-Shot Insider Threat Detection
Insider threats represent a significant challenge in both corporate and governmental sectors.
Most existing supervised learning based detection methods that rely on transforming user …
Most existing supervised learning based detection methods that rely on transforming user …
Insider threat detection based on user behaviour analysis
Insider threat detection is a major challenge for security in organizations. They are the
employees/users of an organization, posing threat to it by performing any malicious activity …
employees/users of an organization, posing threat to it by performing any malicious activity …
A federated and explainable approach for insider threat detection in IoT
An insider threat is a malicious action launched by authorized personnel inside the
organization. Since insider actions may only leave a small digital footprint in the system, it is …
organization. Since insider actions may only leave a small digital footprint in the system, it is …
An approach to internal threats detection based on sentiment analysis and network analysis
Years into the insider threat, it remains an universal challenge to predict and defend.
Concerning this problem, there has been a multitude of solutions, including the detection of …
Concerning this problem, there has been a multitude of solutions, including the detection of …
A novel deep synthesis-based insider intrusion detection (DS-IID) model for malicious insiders and AI-generated threats
Insider threats pose a significant challenge to IT security, particularly with the rise of
generative AI technologies, which can create convincing fake user profiles and mimic …
generative AI technologies, which can create convincing fake user profiles and mimic …