Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
Comparative analysis of intrusion detection systems and machine learning based model analysis through decision tree
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
Anomaly based network intrusion detection for IoT attacks using deep learning technique
Abstract Internet of Things (IoT) applications are growing in popularity for being widely used
in many real-world services. In an IoT ecosystem, many devices are connected with each …
in many real-world services. In an IoT ecosystem, many devices are connected with each …
Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approach
Abstract The Internet of Things (IoT) is currently seeing tremendous growth due to new
technologies and big data. Research in the field of IoT security is an emerging topic. IoT …
technologies and big data. Research in the field of IoT security is an emerging topic. IoT …
An anomaly detection model based on deep auto-encoder and capsule graph convolution via sparrow search algorithm in 6G internet-of-everything
In recent years, driven by the continuous development of mobile Internet technology and
artificial intelligence technology, the improvement of the manufacturing level of 6G Internet …
artificial intelligence technology, the improvement of the manufacturing level of 6G Internet …
Deep learning in medical imaging: A brief review
S Serte, A Serener, F Al‐Turjman - Transactions on Emerging …, 2022 - Wiley Online Library
Researchers have used deep learning methods for a human level or better disease
identification and detection. This paper reports, in brief, the recent work in deep learning …
identification and detection. This paper reports, in brief, the recent work in deep learning …
An ensemble deep learning based IDS for IoT using Lambda architecture
R Alghamdi, M Bellaiche - Cybersecurity, 2023 - Springer
Abstract The Internet of Things (IoT) has revolutionized our world today by providing greater
levels of accessibility, connectivity and ease to our everyday lives. It enables massive …
levels of accessibility, connectivity and ease to our everyday lives. It enables massive …
Integration of deep learning into the iot: A survey of techniques and challenges for real-world applications
The internet of things (IoT) has emerged as a pivotal technological paradigm facilitating
interconnected and intelligent devices across multifarious domains. The proliferation of IoT …
interconnected and intelligent devices across multifarious domains. The proliferation of IoT …
Anomaly‐based intrusion detection systems: The requirements, methods, measurements, and datasets
With the Internet's unprecedented growth and nations' reliance on computer networks, new
cyber‐attacks are created every day as means for achieving financial gain, imposing …
cyber‐attacks are created every day as means for achieving financial gain, imposing …
Improved transformer-based privacy-preserving architecture for intrusion detection in secure v2x communications
The Internet of Vehicles (IoVs) makes communications between numerous devices that use
various protocols susceptible to hacker incursions and attacks, which can compromise …
various protocols susceptible to hacker incursions and attacks, which can compromise …