[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions
R Kaur, D Gabrijelčič, T Klobučar - Information Fusion, 2023 - Elsevier
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
A hybrid intrusion detection model using ega-pso and improved random forest method
AK Balyan, S Ahuja, UK Lilhore, SK Sharma… - Sensors, 2022 - mdpi.com
Due to the rapid growth in IT technology, digital data have increased availability, creating
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
PPSF: A privacy-preserving and secure framework using blockchain-based machine-learning for IoT-driven smart cities
With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of
urbanization. IoT networks allow distributed smart devices to collect and process data within …
urbanization. IoT networks allow distributed smart devices to collect and process data within …
[HTML][HTML] A hybrid CNN+ LSTM-based intrusion detection system for industrial IoT networks
HC Altunay, Z Albayrak - … Science and Technology, an International Journal, 2023 - Elsevier
Abstract The Internet of Things (IoT) ecosystem has proliferated based on the use of the
internet and cloud-based technologies in the industrial area. IoT technology used in the …
internet and cloud-based technologies in the industrial area. IoT technology used in the …
CorrAUC: a malicious bot-IoT traffic detection method in IoT network using machine-learning techniques
Identification of anomaly and malicious traffic in the Internet-of-Things (IoT) network is
essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT …
essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT …
An ensemble learning and fog-cloud architecture-driven cyber-attack detection framework for IoMT networks
Abstract Internet of Medical Things (IoMT), an application of Internet of Things (IoT), is
addressing countless limitation of traditional health-care systems such as quality of patient …
addressing countless limitation of traditional health-care systems such as quality of patient …
Advanced feature extraction and selection approach using deep learning and Aquila optimizer for IoT intrusion detection system
Developing cyber security is very necessary and has attracted considerable attention from
academy and industry organizations worldwide. It is also very necessary to provide …
academy and industry organizations worldwide. It is also very necessary to provide …
A review of recent approaches on wrapper feature selection for intrusion detection
In this paper, we present a review of recent advances in wrapper feature selection
techniques for attack detection and classification, applied in intrusion detection area. Due to …
techniques for attack detection and classification, applied in intrusion detection area. Due to …
Deep learning-enabled anomaly detection for IoT systems
Abstract Internet of Things (IoT) systems have become an intrinsic technology in various
industries and government services. Unfortunately, IoT devices and networks are known to …
industries and government services. Unfortunately, IoT devices and networks are known to …