Cyber risk and cybersecurity: a systematic review of data availability
Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020,
indicating an increase of more than 50% since 2018. With the average cyber insurance …
indicating an increase of more than 50% since 2018. With the average cyber insurance …
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
[HTML][HTML] An insider data leakage detection using one-hot encoding, synthetic minority oversampling and machine learning techniques
Insider threats are malicious acts that can be carried out by an authorized employee within
an organization. Insider threats represent a major cybersecurity challenge for private and …
an organization. Insider threats represent a major cybersecurity challenge for private and …
A survey of large language models for cyber threat detection
With the increasing complexity of cyber threats and the expanding scope of cyberspace,
there exist progressively more challenges in cyber threat detection. It's proven that most …
there exist progressively more challenges in cyber threat detection. It's proven that most …
A new intelligent multilayer framework for insider threat detection
In several earlier studies, machine learning (ML) has been widely used for building insider
threat detection systems. However, the selection of the most appropriate ML classification …
threat detection systems. However, the selection of the most appropriate ML classification …
[HTML][HTML] Insider threat mitigation: Systematic literature review
The increasing prevalence of cybercrime necessitates the implementation of robust security
measures. The majority of these attacks are initiated by authorized users who possess …
measures. The majority of these attacks are initiated by authorized users who possess …
Insider threat detection using machine learning approach
Insider threats pose a critical challenge for securing computer networks and systems. They
are malicious activities by authorised users that can cause extensive damage, such as …
are malicious activities by authorised users that can cause extensive damage, such as …
[HTML][HTML] A new univariate feature selection algorithm based on the best–worst multi-attribute decision-making method
With the extensive applicability of machine learning classification algorithms to a wide
spectrum of domains, feature selection (FS) becomes a relevant data preprocessing …
spectrum of domains, feature selection (FS) becomes a relevant data preprocessing …
Insider threat detection model using anomaly-based isolation forest algorithm
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 …
insiders are authorized users who are acquainted with the business's system, making …
[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 …