[HTML][HTML] A lightweight SEL for attack detection in IoT/IIoT networks
Intrusion detection systems (IDSs) that continuously monitor data flow and take swift action
when attacks are identified safeguard networks. Conventional IDS exhibit limitations, such …
when attacks are identified safeguard networks. Conventional IDS exhibit limitations, such …
Toward improved machine learning-based intrusion detection for Internet of Things traffic
The rapid development of Internet of Things (IoT) networks has revealed multiple security
issues. On the other hand, machine learning (ML) has proven its efficiency in building …
issues. On the other hand, machine learning (ML) has proven its efficiency in building …
A Comprehensive Review of Cyber-Attacks Targeting IoT Systems and Their Security Measures.
ML Mutleg, AM Mahmood… - International Journal of …, 2024 - search.ebscohost.com
Abstract The Internet of Things (IoT) represents the backbone of current and future
technologies. The main objective of IoT is to make human life easier by automating most …
technologies. The main objective of IoT is to make human life easier by automating most …
Cybersecurity anomaly detection: Ai and ethereum blockchain for a secure and tamperproof ioht data management
The Internet of Healthcare Things (IoHT) is an emerging critical technology for managing
patients' health. They are prone to cybersecurity vulnerabilities because they are connected …
patients' health. They are prone to cybersecurity vulnerabilities because they are connected …
DL-SkLSTM approach for cyber security threats detection in 5G enabled IIoT
A Rajak, R Tripathi - International Journal of Information Technology, 2024 - Springer
The advancement of 5G technology has enabled the IIoT (Industrial Internet of Things) to
integrate artificial intelligence, cloud computing, and edge computing in real-time, leading to …
integrate artificial intelligence, cloud computing, and edge computing in real-time, leading to …
Real-time data fusion for intrusion detection in industrial control systems based on cloud computing and big data techniques
Intrusion detection in industrial control systems (ICS) is crucial for maintaining secu rity in
modern industries. However, the rapid growth of data generated from various sources …
modern industries. However, the rapid growth of data generated from various sources …
An end-to-end learning approach for enhancing intrusion detection in Industrial-Internet of Things
Abstract The Industrial-Internet of Things (I-IoT) stands out as one of the most dynamically
evolving subfields within the expansive realm of the Internet of Things (IoT). Its exponential …
evolving subfields within the expansive realm of the Internet of Things (IoT). Its exponential …
The convergence of cybersecurity, Internet of Things (IoT), and data analytics: Safeguarding smart ecosystems
The Internet of Things (IoT) has profoundly impacted various industries by enabling
enhanced connectivity and automation, thereby transforming our interactions with …
enhanced connectivity and automation, thereby transforming our interactions with …
An intrusion detection method combining variational auto-encoder and generative adversarial networks
Z Li, C Huang, W Qiu - Computer Networks, 2024 - Elsevier
Deep learning is a crucial research area in network security, particularly when it comes to
detecting network attacks. While some deep learning algorithms have shown promising …
detecting network attacks. While some deep learning algorithms have shown promising …
Towards a generalized hybrid deep learning model with optimized hyperparameters for malicious traffic detection in the Industrial Internet of Things
B Babayigit, M Abubaker - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Detecting malicious attacks in Industrial Internet of Things (IIoT) is crucial to minimize
downtime and financial losses. However, existing deep learning (DL) research faces …
downtime and financial losses. However, existing deep learning (DL) research faces …