Security and privacy in metaverse: A comprehensive survey
Metaverse describes a new shape of cyberspace and has become a hot-trending word since
2021. There are many explanations about what Meterverse is and attempts to provide a …
2021. There are many explanations about what Meterverse is and attempts to provide a …
Detecting and preventing cyber insider threats: A survey
Information communications technology systems are facing an increasing number of cyber
security threats, the majority of which are originated by insiders. As insiders reside behind …
security threats, the majority of which are originated by insiders. As insiders reside behind …
An insider data leakage detection using one-hot encoding, synthetic minority oversampling and machine learning techniques
T Al-Shehari, RA Alsowail - Entropy, 2021 - mdpi.com
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 …
Insight into insiders and it: A survey of insider threat taxonomies, analysis, modeling, and countermeasures
Insider threats are one of today's most challenging cybersecurity issues that are not well
addressed by commonly employed security solutions. In this work, we propose structural …
addressed by commonly employed security solutions. In this work, we propose structural …
Enterprise data breach: causes, challenges, prevention, and future directions
A data breach is the intentional or inadvertent exposure of confidential information to
unauthorized parties. In the digital era, data has become one of the most critical components …
unauthorized parties. In the digital era, data has become one of the most critical components …
AI^ 2: training a big data machine to defend
K Veeramachaneni, I Arnaldo… - 2016 IEEE 2nd …, 2016 - ieeexplore.ieee.org
We present AI2, an analyst-in-the-loop security system where Analyst Intuition (AI) is put
together with state-of-the-art machine learning to build a complete end-to-end Artificially …
together with state-of-the-art machine learning to build a complete end-to-end Artificially …
Analyzing data granularity levels for insider threat detection using machine learning
DC Le, N Zincir-Heywood… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Malicious insider attacks represent one of the most damaging threats to networked systems
of companies and government agencies. There is a unique set of challenges that come with …
of companies and government agencies. There is a unique set of challenges that come with …
Anomaly detection for insider threats using unsupervised ensembles
DC Le, N Zincir-Heywood - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
Insider threat represents a major cybersecurity challenge to companies, organizations, and
government agencies. Insider threat detection involves many challenges, including …
government agencies. Insider threat detection involves many challenges, including …
A new take on detecting insider threats: exploring the use of hidden markov models
The threat that malicious insiders pose towards organisations is a significant problem. In this
paper, we investigate the task of detecting such insiders through a novel method of …
paper, we investigate the task of detecting such insiders through a novel method of …
Incorporating expert feedback into active anomaly discovery
Unsupervised anomaly detection algorithms search for outliers and then predict that these
outliers are the anomalies. When deployed, however, these algorithms are often criticized …
outliers are the anomalies. When deployed, however, these algorithms are often criticized …