Network intrusion detection for IoT security based on learning techniques
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
[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 …
A deep learning approach to network intrusion detection
Network intrusion detection systems (NIDSs) play a crucial role in defending computer
networks. However, there are concerns regarding the feasibility and sustainability of current …
networks. However, there are concerns regarding the feasibility and sustainability of current …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
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 …
Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
A survey of machine learning techniques applied to software defined networking (SDN): Research issues and challenges
In recent years, with the rapid development of current Internet and mobile communication
technologies, the infrastructure, devices and resources in networking systems are becoming …
technologies, the infrastructure, devices and resources in networking systems are becoming …
Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues
A Aldweesh, A Derhab, AZ Emam - Knowledge-Based Systems, 2020 - Elsevier
The massive growth of data that are transmitted through a variety of devices and
communication protocols have raised serious security concerns, which have increased the …
communication protocols have raised serious security concerns, which have increased the …
Deep learning for intelligent wireless networks: A comprehensive survey
As a promising machine learning tool to handle the accurate pattern recognition from
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …
Deep learning methods in network intrusion detection: A survey and an objective comparison
The use of deep learning models for the network intrusion detection task has been an active
area of research in cybersecurity. Although several excellent surveys cover the growing …
area of research in cybersecurity. Although several excellent surveys cover the growing …