ToN_IoT: The role of heterogeneity and the need for standardization of features and attack types in IoT network intrusion data sets
The Internet of Things (IoT) is reshaping our connected world as the number of lightweight
devices connected to the Internet is rapidly growing. Therefore, high-quality research on …
devices connected to the Internet is rapidly growing. Therefore, high-quality research on …
[HTML][HTML] Using embedded feature selection and CNN for classification on CCD-INID-V1—a new IoT dataset
As Internet of Things (IoT) networks expand globally with an annual increase of active
devices, providing better safeguards to threats is becoming more prominent. An intrusion …
devices, providing better safeguards to threats is becoming more prominent. An intrusion …
A novel sdn dataset for intrusion detection in iot networks
AK Sarica, P Angin - 2020 16th International Conference on …, 2020 - ieeexplore.ieee.org
The number of Internet of Things (IoT) devices and the use cases they aim to support have
increased sharply in the past decade with the rapid developments in wireless networking …
increased sharply in the past decade with the rapid developments in wireless networking …
[HTML][HTML] Approach for detecting attacks on IoT networks based on ensemble feature selection and deep learning models
The Internet of Things (IoT) has transformed our interaction with technology and introduced
security challenges. The growing number of IoT attacks poses a significant threat to …
security challenges. The growing number of IoT attacks poses a significant threat to …
[HTML][HTML] Examining the suitability of NetFlow features in detecting IoT network intrusions
The past few years have witnessed a substantial increase in cyberattacks on Internet of
Things (IoT) devices and their networks. Such attacks pose a significant threat to …
Things (IoT) devices and their networks. Such attacks pose a significant threat to …
DFE: efficient IoT network intrusion detection using deep feature extraction
A Basati, MM Faghih - Neural Computing and Applications, 2022 - Springer
In recent years, the Internet of Things (IoT) has received a lot of attention. It has been used in
many applications such as the control industry, industrial plants, and medicine. In this …
many applications such as the control industry, industrial plants, and medicine. In this …
FSO-LSTM IDS: hybrid optimized and ensembled deep-learning network-based intrusion detection system for smart networks.
AS Alqahtani - Journal of Supercomputing, 2022 - search.ebscohost.com
Abstract The Internet of Things (IoT) has achieved exponential growth worldwide. Although
the IoT is used by millions of users, these networks are handicapped by attacks such as …
the IoT is used by millions of users, these networks are handicapped by attacks such as …
Internet of things (IoT) security dataset evolution: Challenges and future directions
The evolution of mobile technologies has introduced smarter and more connected objects
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
Deep learning-based intrusion detection for IoT networks
Internet of Things (IoT) has an immense potential for a plethora of applications ranging from
healthcare automation to defence networks and the power grid. The security of an IoT …
healthcare automation to defence networks and the power grid. The security of an IoT …
[HTML][HTML] CNN-CNN: Dual Convolutional Neural Network Approach for Feature Selection and Attack Detection on Internet of Things Networks
The Internet of Things (IoT) has brought significant advancements that have connected our
world more closely than ever before. However, the growing number of connected devices …
world more closely than ever before. However, the growing number of connected devices …