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 …
Machine learning based insider threat modelling and detection
DC Le, AN Zincir-Heywood - 2019 IFIP/IEEE Symposium on …, 2019 - ieeexplore.ieee.org
Recently, malicious insider attacks represent one of the most damaging threats to
companies and government agencies. This paper proposes a new framework in …
companies and government agencies. This paper proposes a new framework in …
Enhancing false negative and positive rates for efficient insider threat detection
M AlSlaiman, MI Salman, MM Saleh, B Wang - Computers & Security, 2023 - Elsevier
Insider threats on information security can become a burden for organizations. However,
outsider attacks have received more attention compared to insider attacks. Many …
outsider attacks have received more attention compared to insider attacks. Many …
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 …
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 …
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 …
Exploring anomalous behaviour detection and classification for insider threat identification
DC Le, N Zincir‐Heywood - International Journal of Network …, 2021 - Wiley Online Library
Recently, malicious insider threats represent one of the most damaging threats to
companies and government agencies. Insider threat detection is a highly skewed data …
companies and government agencies. Insider threat detection is a highly skewed data …
A review of insider threat detection approaches with IoT perspective
Security professionals, government agencies, and corporate organizations have found an
inherent need to prevent or mitigate attacks from insider threats. Accordingly, active research …
inherent need to prevent or mitigate attacks from insider threats. Accordingly, active research …
Malicious insider attack detection in IoTs using data analytics
Internet of Things (IoTs) are set to revolutionize our lives and are widely being adopted
nowadays. The IoT devices have a range of applications including smart homes, smart …
nowadays. The IoT devices have a range of applications including smart homes, smart …
Exploring feature normalization and temporal information for machine learning based insider threat detection
P Ferreira, DC Le… - 2019 15th International …, 2019 - ieeexplore.ieee.org
Insider threat is one of the most damaging cyber security attacks to companies and
organizations. In this paper, we explore different techniques to leverage spatial and …
organizations. In this paper, we explore different techniques to leverage spatial and …