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[HTML][HTML] Machine learning and deep learning methods for intrusion detection systems: A survey
H Liu, B Lang - applied sciences, 2019 - mdpi.com
Networks play important roles in modern life, and cyber security has become a vital research
area. An intrusion detection system (IDS) which is an important cyber security technique …
area. An intrusion detection system (IDS) which is an important cyber security technique …
[HTML][HTML] Intrusion detection in internet of things systems: a review on design approaches leveraging multi-access edge computing, machine learning, and datasets
The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic
increase of network data and placed a high computation complexity across various …
increase of network data and placed a high computation complexity across various …
[HTML][HTML] 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 …
Machine learning models for secure data analytics: A taxonomy and threat model
In recent years, rapid technological advancements in smart devices and their usage in a
wide range of applications exponentially increases the data generated from these devices …
wide range of applications exponentially increases the data generated from these devices …
A new solution for cyber security in big data using machine learning approach
The information management System works on the incident association, used to track and
identify previously established threats, and is no longer suitable due to variants in the …
identify previously established threats, and is no longer suitable due to variants in the …
[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 …
Detection and prediction of insider threats to cyber security: a systematic literature review and meta-analysis
Cyber security is vital to the success of today's digital economy. The major security threats
are coming from within, as opposed to outside forces. Insider threat detection and prediction …
are coming from within, as opposed to outside forces. Insider threat detection and prediction …
[HTML][HTML] Insider threat detection based on user behavior modeling and anomaly detection algorithms
Insider threats are malicious activities by authorized users, such as theft of intellectual
property or security information, fraud, and sabotage. Although the number of insider threats …
property or security information, fraud, and sabotage. Although the number of insider threats …
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 …