Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review

H Kheddar, Y Himeur, AI Awad - Journal of Network and Computer …, 2023 - Elsevier
Globally, the external internet is increasingly being connected to industrial control systems.
As a result, there is an immediate need to protect these networks from a variety of threats …

Machine learning and deep learning techniques for internet of things network anomaly detection—current research trends

SH Rafique, A Abdallah, NS Musa, T Murugan - Sensors, 2024 - mdpi.com
With its exponential growth, the Internet of Things (IoT) has produced unprecedented levels
of connectivity and data. Anomaly detection is a security feature that identifies instances in …

Heterogeneous domain adaptation for IoT intrusion detection: A geometric graph alignment approach

J Wu, H Dai, Y Wang, K Ye, C Xu - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Data scarcity hinders the usability of data-dependent algorithms when tackling IoT intrusion
detection (IID). To address this, we utilize the data-rich network intrusion detection (NID) …

Multi-source refined adversarial domain adaptation with transfer complementarity infusion for IoT intrusion detection under limited samples

K Li, W Ma, H Duan, H **e - Expert Systems with Applications, 2024 - Elsevier
The arrival of 5G has facilitated further development of the Internet of Things (IoT) which is
vulnerable to hacking because of its widespread use. Large networks oriented toward …

[PDF][PDF] Deep transfer learning applications in intrusion detection systems: A comprehensive review

H Kheddar, Y Himeur, AI Awad - arxiv preprint arxiv …, 2023 - research.uaeu.ac.ae
Globally, the external Internet is increasingly being connected to the contemporary industrial
control system. As a result, there is an immediate need to protect the network from several …

Novel Intrusion Detection Strategies With Optimal Hyper Parameters for Industrial Internet of Things Based On Stochastic Games and Double Deep Q-Networks

S Yu, X Wang, Y Shen, G Wu, S Yu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) has experienced rapid growth in recent years, with an
increasing number of interconnected devices, thereby expanding the attack surface …

Emtd-ssc: An enhanced malicious traffic detection model using transfer learning under small sample conditions in iot

Y Ge, Y Gao, X Li, B Cai, J **… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
In the Internet of Things (IoT) scenario, the device diversity and data sparsity present a
significant challenge for malicious traffic detection, notably the “small sample problem” …

A Domain Adaptive IoT Intrusion Detection Algorithm Based on GWR-GCN Feature Extraction and Conditional Domain Adversary

Q Wang, X Wang, H Liu, Y Wang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In the field of Internet of Things (IoT), the intrusion detection data is scarce because of the
network security and privacy. This article proposes a domain adaptive IoT intrusion detection …

An autoencoder-based hybrid detection model for intrusion detection with small-sample problem

N Wei, L Yin, J Tan, C Ruan, C Yin… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Cyber-attacks have become more frequent, targeted, and complex as the exponential
growth in computer networks and the development of Internet of Things (IoT). Network …

A novel DAG-blockchain structure for trusted routing in secure MANET-IoT environment

N Ilakkiya, A Rajaram - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
Different physical objects can be employed in the modern technological environment to
facilitate human activity. In order to connect physical objects with the universe of digital using …