Detecting cybersecurity attacks in internet of things using artificial intelligence methods: A systematic literature review
M Abdullahi, Y Baashar, H Alhussian, A Alwadain… - Electronics, 2022 - mdpi.com
In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0),
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …
Internet of Things intrusion detection systems: a comprehensive review and future directions
A Heidari, MA Jabraeil Jamali - Cluster Computing, 2023 - Springer
Abstract The Internet of Things (IoT) is a paradigm that connects objects to the Internet as a
whole and enables them to work together to achieve common objectives, such as innovative …
whole and enables them to work together to achieve common objectives, such as innovative …
Anomaly-based intrusion detection systems in iot using deep learning: A systematic literature review
The Internet of Things (IoT) concept has emerged to improve people's lives by providing a
wide range of smart and connected devices and applications in several domains, such as …
wide range of smart and connected devices and applications in several domains, such as …
Zero-day attack detection: a systematic literature review
With the continuous increase in cyberattacks over the past few decades, the quest to
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …
E-sfd: Explainable sensor fault detection in the ics anomaly detection system
C Hwang, T Lee - IEEE Access, 2021 - ieeexplore.ieee.org
Industrial Control Systems (ICS) are evolving into smart environments with increased
interconnectivity by being connected to the Internet. These changes increase the likelihood …
interconnectivity by being connected to the Internet. These changes increase the likelihood …
Optimized deep autoencoder model for internet of things intruder detection
B Lahasan, H Samma - IEEE Access, 2022 - ieeexplore.ieee.org
The development of an optimized deep learning intruder detection model that could be
executed on IoT devices with limited hardware support has several advantages, such as the …
executed on IoT devices with limited hardware support has several advantages, such as the …
A deep learning ensemble approach to detecting unknown network attacks
The majority of the intrusion detection solutions proposed using machine learning and deep
learning approaches are based on known attack classes only. Comprehensive threat …
learning approaches are based on known attack classes only. Comprehensive threat …
[HTML][HTML] Performance evaluation of a fast and efficient intrusion detection framework for advanced persistent threat-based cyberattacks
NE Park, YR Lee, S Joo, SY Kim, SH Kim… - Computers and …, 2023 - Elsevier
After the COVID-19 pandemic, cyberattacks are increasing as non-face-to-face
environments such as telecommuting and telemedicine proliferate. Cyberattackers exploit …
environments such as telecommuting and telemedicine proliferate. Cyberattackers exploit …
[图书][B] Machine learning for cybersecurity: Innovative deep learning solutions
M Omar - 2022 - books.google.com
This SpringerBrief presents the underlying principles of machine learning and how to deploy
various deep learning tools and techniques to tackle and solve certain challenges facing the …
various deep learning tools and techniques to tackle and solve certain challenges facing the …
HEOD: Human-assisted ensemble outlier detection for cybersecurity
Despite extensive academic research in anomaly detection within the cybersecurity domain,
its successful adoption in real-world settings remains limited. This paper addresses the …
its successful adoption in real-world settings remains limited. This paper addresses the …