Adversarial machine learning for network intrusion detection systems: A comprehensive survey
Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …
network attacks that compromise the security of the data, systems, and networks. In recent …
Internet of things (iot) security intelligence: a comprehensive overview, machine learning solutions and research directions
Abstract The Internet of Things (IoT) is one of the most widely used technologies today, and
it has a significant effect on our lives in a variety of ways, including social, commercial, and …
it has a significant effect on our lives in a variety of ways, including social, commercial, and …
Edge-IIoTset: A new comprehensive realistic cyber security dataset of IoT and IIoT applications for centralized and federated learning
In this paper, we propose a new comprehensive realistic cyber security dataset of IoT and
IIoT applications, called Edge-IIoTset, which can be used by machine learning-based …
IIoT applications, called Edge-IIoTset, which can be used by machine learning-based …
Anomaly-based intrusion detection system for IoT networks through deep learning model
Abstract The Internet of Things (IoT) idea has been developed to enhance people's lives by
delivering a diverse range of smart interconnected devices and applications in several …
delivering a diverse range of smart interconnected devices and applications in several …
CICIoT2023: A real-time dataset and benchmark for large-scale attacks in IoT environment
Nowadays, the Internet of Things (IoT) concept plays a pivotal role in society and brings new
capabilities to different industries. The number of IoT solutions in areas such as …
capabilities to different industries. The number of IoT solutions in areas such as …
Machine learning: Algorithms, real-world applications and research directions
IH Sarker - SN computer science, 2021 - Springer
In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …
[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
threatening. Network intrusion detection has been widely accepted as an effective method to …
Deep learning based attack detection for cyber-physical system cybersecurity: A survey
With the booming of cyber attacks and cyber criminals against cyber-physical systems
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …
A new distributed architecture for evaluating AI-based security systems at the edge: Network TON_IoT datasets
N Moustafa - Sustainable Cities and Society, 2021 - Elsevier
While there has been a significant interest in understanding the cyber threat landscape of
Internet of Things (IoT) networks, and the design of Artificial Intelligence (AI)-based security …
Internet of Things (IoT) networks, and the design of Artificial Intelligence (AI)-based security …
Explainable artificial intelligence applications in cyber security: State-of-the-art in research
This survey presents a comprehensive review of current literature on Explainable Artificial
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …