Federated learning for intrusion detection system: Concepts, challenges and future directions

S Agrawal, S Sarkar, O Aouedi, G Yenduri… - Computer …, 2022 - Elsevier
The rapid development of the Internet and smart devices trigger surge in network traffic
making its infrastructure more complex and heterogeneous. The predominated usage of …

A Comprehensive Survey on Machine Learning‐Based Intrusion Detection Systems for Secure Communication in Internet of Things

SVN Santhosh Kumar, M Selvi… - Computational …, 2023 - Wiley Online Library
The Internet of Things (IoT) is a distributed system which is made up of the connections of
smart objects (things) that can continuously sense the events in their sensing domain and …

A deep learning method with wrapper based feature extraction for wireless intrusion detection system

SM Kasongo, Y Sun - Computers & Security, 2020 - Elsevier
In the past decade, wired and wireless computer networks have substantially evolved
because of the rapid development of technologies such as the Internet of Things (IoT) …

Robust detection for network intrusion of industrial IoT based on multi-CNN fusion

Y Li, Y Xu, Z Liu, H Hou, Y Zheng, Y Xin, Y Zhao, L Cui - Measurement, 2020 - Elsevier
A robust intrusion detection system plays a very important role in network security. In the
face of complex network data and diverse intrusion methods, traditional machine learning …

A comprehensive systematic literature review on intrusion detection systems

M Ozkan-Okay, R Samet, Ö Aslan, D Gupta - IEEE Access, 2021 - ieeexplore.ieee.org
Effectively detecting intrusions in the computer networks still remains problematic. This is
because cyber attackers are changing packet contents to disguise the intrusion detection …

A unified architectural approach for cyberattack-resilient industrial control systems

C Zhou, B Hu, Y Shi, YC Tian, X Li… - Proceedings of the …, 2020 - ieeexplore.ieee.org
With the rapid development of functional requirements in the emerging Industry 4.0 era,
modern industrial control systems (ICSs) are no longer isolated islands, making them more …

[HTML][HTML] IDS-INT: Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

F Ullah, S Ullah, G Srivastava, JCW Lin - Digital Communications and …, 2024 - Elsevier
A network intrusion detection system is critical for cyber security against illegitimate attacks.
In terms of feature perspectives, network traffic may include a variety of elements such as …

An intrusion identification and prevention for cloud computing: From the perspective of deep learning

A Kumar, RS Umurzoqovich, ND Duong, P Kanani… - Optik, 2022 - Elsevier
As the Internet industry has connected the globe using advancements in computer network
from LAN to Cloud Infrastructure, Fashions and Developments in Internet of Things (IoT) …

Darknet traffic big-data analysis and network management for real-time automating of the malicious intent detection process by a weight agnostic neural networks …

K Demertzis, K Tsiknas, D Takezis, C Skianis, L Iliadis - Electronics, 2021 - mdpi.com
Attackers are perpetually modifying their tactics to avoid detection and frequently leverage
legitimate credentials with trusted tools already deployed in a network environment, making …

DRaNN: A deep random neural network model for intrusion detection in industrial IoT

S Latif, Z Idrees, Z Zou, J Ahmad - … international conference on …, 2020 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT) has arisen as an emerging trend in the industrial sector.
Millions of sensors present in IIoT networks generate a massive amount of data that can …