[HTML][HTML] Cyber threat intelligence using PCA-DNN model to detect abnormal network behavior

M Al-Fawa'reh, M Al-Fayoumi, S Nashwan… - Egyptian Informatics …, 2022 - Elsevier
Security issues are the most critical challenges facing new technologies associated with the
internet of things (IoT), big data, and cloud computing. A secure and efficient intrusion …

M-MultiSVM: An efficient feature selection assisted network intrusion detection system using machine learning

AV Turukmane, R Devendiran - Computers & Security, 2024 - Elsevier
The intrusions are increasing daily, so there is a huge amount of privacy violations, financial
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …

[HTML][HTML] 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 …

Developing new deep-learning model to enhance network intrusion classification

H Azzaoui, AZE Boukhamla, D Arroyo, A Bensayah - Evolving Systems, 2022 - Springer
Network traffic has recently known tremendous growth, and it is set to explode over the next
few years. Alongside the increase in traffic, network attacks have become more complex …

A regularized cross-layer ladder network for intrusion detection in industrial internet of things

J Long, W Liang, KC Li, Y Wei… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As part of Big Data trends, the ubiquitous use of the Internet of Things (IoT) in the industrial
environment has generated a significant amount of network traffic. In this type of IoT …

Intrusion detection system based on fast hierarchical deep convolutional neural network

RV Mendonça, AAM Teodoro, RL Rosa, M Saadi… - IEEE …, 2021 - ieeexplore.ieee.org
Currently, with the increasing number of devices connected to the Internet, search for
network vulnerabilities to attackers has increased, and protection systems have become …

[PDF][PDF] DeepIoT. IDS: Hybrid deep learning for enhancing IoT network intrusion detection

ZK Maseer, R Yusof, SA Mostafa, N Bahaman… - Comput. Mater …, 2021 - eprints.utm.my
With an increasing number of services connected to the internet, including cloud computing
and Internet of Things (IoT) systems, the prevention of cyberattacks has become more …

[HTML][HTML] Detecting cybersecurity attacks across different network features and learners

JL Leevy, J Hancock, R Zuech, TM Khoshgoftaar - Journal of Big Data, 2021 - Springer
Abstract Machine learning algorithms efficiently trained on intrusion detection datasets can
detect network traffic capable of jeopardizing an information system. In this study, we use the …

InSDN: A novel SDN intrusion dataset

MS Elsayed, NA Le-Khac, AD Jurcut - IEEE access, 2020 - ieeexplore.ieee.org
Software-Defined Network (SDN) has been developed to reduce network complexity
through control and manage the whole network from a centralized location. Today, SDN is …

A hybrid intrusion detection system based on feature selection and weighted stacking classifier

R Zhao, Y Mu, L Zou, X Wen - IEEE Access, 2022 - ieeexplore.ieee.org
Cyber-attacks occur more frequently with the rapid growth in the Internet. Intrusion detection
systems (IDS) have become an important part of protecting system security. There are still …