[HTML][HTML] 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 …
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 …
[HTML][HTML] IoT anomaly detection methods and applications: A survey
A Chatterjee, BS Ahmed - Internet of Things, 2022 - Elsevier
Ongoing research on anomaly detection for the Internet of Things (IoT) is a rapidly
expanding field. This growth necessitates an examination of application trends and current …
expanding field. This growth necessitates an examination of application trends and current …
IoT intrusion detection using machine learning with a novel high performing feature selection method
The Internet of Things (IoT) ecosystem has experienced significant growth in data traffic and
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
Machine-learning-based darknet traffic detection system for IoT applications
The massive modern technical revolution in electronics, cognitive computing, and sensing
has provided critical infrastructure for the development of today's Internet of Things (IoT) for a …
has provided critical infrastructure for the development of today's Internet of Things (IoT) for a …
Comparative research on network intrusion detection methods based on machine learning
C Zhang, D Jia, L Wang, W Wang, F Liu, A Yang - Computers & Security, 2022 - Elsevier
Network intrusion detection system is an essential part of network security research. It
detects intrusion behaviors through active defense technology and takes emergency …
detects intrusion behaviors through active defense technology and takes emergency …
lIDS-SIoEL: intrusion detection framework for IoT-based smart environments security using ensemble learning
Smart cities are being enabled all around the world by Internet of Things (IoT) applications.
A smart city idea necessitates the integration of information and communication …
A smart city idea necessitates the integration of information and communication …
ELBA-IoT: An ensemble learning model for botnet attack detection in IoT networks
Q Abu Al-Haija, M Al-Dala'ien - Journal of Sensor and Actuator Networks, 2022 - mdpi.com
Due to the prompt expansion and development of intelligent systems and autonomous,
energy-aware sensing devices, the Internet of Things (IoT) has remarkably grown and …
energy-aware sensing devices, the Internet of Things (IoT) has remarkably grown and …
[HTML][HTML] Deep learning-based intrusion detection approach for securing industrial Internet of Things
S Soliman, W Oudah, A Aljuhani - Alexandria Engineering Journal, 2023 - Elsevier
The widespread deployment of the Internet of Things (IoT) into critical sectors such as
industrial and manufacturing has resulted in the Industrial Internet of Things (IIoT). The IIoT …
industrial and manufacturing has resulted in the Industrial Internet of Things (IIoT). The IIoT …
High-performance intrusion detection system for networked UAVs via deep learning
Q Abu Al-Haija, A Al Badawi - Neural Computing and Applications, 2022 - Springer
Abstract Recently, Unmanned Aerial Vehicles (UAVs) have become a widely popular
technology with remarkable growth and unprecedented attention. However, UAV …
technology with remarkable growth and unprecedented attention. However, UAV …