Intrusion detection systems for IoT based on bio-inspired and machine learning techniques: a systematic review of the literature

R Saadouni, C Gherbi, Z Aliouat, Y Harbi, A Khacha - Cluster Computing, 2024 - Springer
Recent technological advancements have significantly expanded both networks and data,
thereby introducing new forms of attacks that pose considerable challenges to intrusion …

Cloud network anomaly detection using machine and deep learning techniques-recent research advancements

A Abdallah, A Alkaabi, G Alameri, SH Rafique… - IEEE …, 2024 - ieeexplore.ieee.org
In the rapidly evolving landscape of computing and networking, the concepts of cloud
networks have gained significant prominence. Although the cloud network offers on-demand …

[HTML][HTML] Golden jackal optimization algorithm with deep learning assisted intrusion detection system for network security

NO Aljehane, HA Mengash, MM Eltahir… - Alexandria Engineering …, 2024 - Elsevier
Network security is essential to our daily communications and networks. Cybersecurity
researchers initiate the significance of emerging proficient network intrusion detection …

Building a cloud-IDS by hybrid bio-inspired feature selection algorithms along with random forest model

M Bakro, RR Kumar, M Husain, Z Ashraf, A Ali… - IEEE …, 2024 - ieeexplore.ieee.org
The adoption of cloud computing has become increasingly widespread across various
domains. However, the inherent security vulnerabilities of cloud computing pose significant …

A Novel hybrid feature selection with cascaded LSTM: Enhancing security in IoT networks

K Sundaram, Y Natarajan… - Wireless …, 2024 - Wiley Online Library
The rapid growth of the Internet of Things (IoT) has created a situation where a huge amount
of sensitive data is constantly being created and sent through many devices, making data …

Improving performance of intrusion detection using ALO selected features and GRU Network

K Sundaram, S Subramanian, Y Natarajan… - SN Computer …, 2023 - Springer
The expansion of the internet has not only opened up new possibilities for cooperation,
networking, and ingenuity, but also presented fresh security hazards and complexities. As …

Using feature selection enhancement to evaluate attack detection in the internet of things environment

K Harahsheh, R Al-Naimat, CH Chen - Electronics, 2024 - mdpi.com
The rapid evolution of technology has given rise to a connected world where billions of
devices interact seamlessly, forming what is known as the Internet of Things (IoT). While the …

Machine learning based network intrusion detection optimization for cloud computing environments

JK Samriya, S Kumar, M Kumar, H Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Cloud computing is an emerging choice among businesses all over the world since it
provides flexible and world wide Web computer capabilities as a customizable service …

[HTML][HTML] Interrelated dynamic biased feature selection and classification model using enhanced gorilla troops optimizer for intrusion detection

A Grandhi, SK Singh - Alexandria Engineering Journal, 2025 - Elsevier
Abstract An Intrusion Detection System (IDS) is a valuable tool for network security since it
can identify attacks, intrusions, and other types of illegal access. Excessive and irrelevant …

Performance metrics of an intrusion detection system through Window-Based Deep Learning models

F Isiaka - Journal of Data Science and Intelligent Systems, 2024 - ojs.bonviewpress.com
Intrusion and prevention technologies perform reliably in harsh conditions by fortifying many
of the world's highest security sites with few defects in high performance. This paper aims to …