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 …
A holistic review of cybersecurity and reliability perspectives in smart airports
Advances in the Internet of Things (IoT) and aviation sector have resulted in the emergence
of smart airports. Services and systems powered by the IoT enable smart airports to have …
of smart airports. Services and systems powered by the IoT enable smart airports to have …
Federated deep learning for zero-day botnet attack detection in IoT-edge devices
Deep learning (DL) has been widely proposed for botnet attack detection in Internet of
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis
In this article, we present a comprehensive study with an experimental analysis of federated
deep learning approaches for cyber security in the Internet of Things (IoT) applications …
deep learning approaches for cyber security in the Internet of Things (IoT) applications …
Deep learning-based intrusion detection for distributed denial of service attack in agriculture 4.0
Smart Agriculture or Agricultural Internet of things, consists of integrating advanced
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
Intrusion detection in the iot under data and concept drifts: Online deep learning approach
OA Wahab - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Although the existing machine learning-based intrusion detection systems in the Internet of
Things (IoT) usually perform well in static environments, they struggle to preserve their …
Things (IoT) usually perform well in static environments, they struggle to preserve their …
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 …
[HTML][HTML] 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 …
An advanced intrusion detection system for IIoT based on GA and tree based algorithms
SM Kasongo - IEEE Access, 2021 - ieeexplore.ieee.org
The evolution of the Internet and cloud-based technologies have empowered several
organizations with the capacity to implement large-scale Internet of Things (IoT)-based …
organizations with the capacity to implement large-scale Internet of Things (IoT)-based …
smote-drnn: A deep learning algorithm for botnet detection in the internet-of-things networks
Nowadays, hackers take illegal advantage of distributed resources in a network of
computing devices (ie, botnet) to launch cyberattacks against the Internet of Things (IoT) …
computing devices (ie, botnet) to launch cyberattacks against the Internet of Things (IoT) …