Explainable intrusion detection for cyber defences in the internet of things: Opportunities and solutions
The field of Explainable Artificial Intelligence (XAI) has garnered considerable research
attention in recent years, aiming to provide interpretability and confidence to the inner …
attention in recent years, aiming to provide interpretability and confidence to the inner …
Machine learning and deep learning approaches for cybersecurity: A review
The rapid evolution and growth of the internet through the last decades led to more concern
about cyber-attacks that are continuously increasing and changing. As a result, an effective …
about cyber-attacks that are continuously increasing and changing. As a result, an effective …
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 …
An effective intrusion detection approach using SVM with naïve Bayes feature embedding
J Gu, S Lu - Computers & Security, 2021 - Elsevier
Network security has become increasingly important in recent decades, while intrusion
detection system plays a critical role in protecting it. Various machine learning techniques …
detection system plays a critical role in protecting it. Various machine learning techniques …
[HTML][HTML] An explainable deep learning-enabled intrusion detection framework in IoT networks
Although the field of eXplainable Artificial Intelligence (XAI) has a significant interest these
days, its implementation within cyber security applications still needs further investigation to …
days, its implementation within cyber security applications still needs further investigation to …
TON_IoT telemetry dataset: A new generation dataset of IoT and IIoT for data-driven intrusion detection systems
Although the Internet of Things (IoT) can increase efficiency and productivity through
intelligent and remote management, it also increases the risk of cyber-attacks. The potential …
intelligent and remote management, it also increases the risk of cyber-attacks. The potential …
Attack classification of an intrusion detection system using deep learning and hyperparameter optimization
A network intrusion detection system (NIDS) is a solution that mitigates the threat of attacks
on a network. The success of a NIDS depends on the success of its algorithm and the …
on a network. The success of a NIDS depends on the success of its algorithm and the …
Intrusion Detection in Industrial Internet of Things Network‐Based on Deep Learning Model with Rule‐Based Feature Selection
The Industrial Internet of Things (IIoT) is a recent research area that links digital equipment
and services to physical systems. The IIoT has been used to generate large quantities of …
and services to physical systems. The IIoT has been used to generate large quantities of …
Multi-dimensional feature fusion and stacking ensemble mechanism for network intrusion detection
A robust network intrusion detection system (NIDS) plays an important role in cyberspace
security for protecting confidential systems from potential threats. In real world network, there …
security for protecting confidential systems from potential threats. In real world network, there …
Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments
Over the last few years, Software Defined Networking (SDN) paradigm has become an
emerging architecture to design future networks and to meet new application demands. SDN …
emerging architecture to design future networks and to meet new application demands. SDN …