[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 …
Machine learning approaches to IoT security: A systematic literature review
With the continuous expansion and evolution of IoT applications, attacks on those IoT
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …
[HTML][HTML] An experimental analysis of attack classification using machine learning in IoT networks
In recent years, there has been a massive increase in the amount of Internet of Things (IoT)
devices as well as the data generated by such devices. The participating devices in IoT …
devices as well as the data generated by such devices. The participating devices in IoT …
[HTML][HTML] An ensemble deep learning model for cyber threat hunting in industrial internet of things
By the emergence of the fourth industrial revolution, interconnected devices and sensors
generate large-scale, dynamic, and inharmonious data in Industrial Internet of Things (IIoT) …
generate large-scale, dynamic, and inharmonious data in Industrial Internet of Things (IIoT) …
[HTML][HTML] XGBoost for imbalanced multiclass classification-based industrial internet of things intrusion detection systems
The Industrial Internet of Things (IIoT) has advanced digital technology and the fastest
interconnection, which creates opportunities to substantially grow industrial businesses …
interconnection, which creates opportunities to substantially grow industrial businesses …
[PDF][PDF] Attack and anomaly detection in iot networks using machine learning techniques: A review
SH Haji, SY Ameen - Asian J. Res. Comput. Sci, 2021 - researchgate.net
ABSTRACT The Internet of Things (IoT) is one of today's most rapidly growing technologies.
It is a technology that allows billions of smart devices or objects known as" Things" to collect …
It is a technology that allows billions of smart devices or objects known as" Things" to collect …
Analysis of machine learning classifiers for early detection of DDoS attacks on IoT devices
Distributed denial-of-service attacks are still difficult to handle as per current scenarios. The
attack aim is a menace to network security and exhausting the target networks with …
attack aim is a menace to network security and exhausting the target networks with …
A comprehensive deep learning benchmark for IoT IDS
The significance of an intrusion detection system (IDS) in networks security cannot be
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …
[HTML][HTML] Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review
Abstract Internet of Things (IoT) driven systems have been sharply growing in the recent
times but this evolution is hampered by cybersecurity threats like spoofing, denial of service …
times but this evolution is hampered by cybersecurity threats like spoofing, denial of service …
A systematic analysis of deep learning methods and potential attacks in internet-of-things surfaces
The usage of intelligent IoT devices is exponentially rising, and so the possibility of attacks in
the IoT surfaces. The deep leaning algorithms are competent for directing the sanctuary …
the IoT surfaces. The deep leaning algorithms are competent for directing the sanctuary …