An anomaly detection model for IoT networks based on flow and flag features using a feed-forward neural network

I Ullah, QH Mahmoud - 2022 IEEE 19th Annual Consumer …, 2022 - ieeexplore.ieee.org
The security of IoT networks is becoming increasingly challenging, and anomaly detection
for IoT network traffic is a critical technique for addressing this issue. However, extracting …

An intrusion detection model using election-based feature selection and K-NN

M Mohy-eddine, A Guezzaz, S Benkirane… - Microprocessors and …, 2023 - Elsevier
Abstract The Internet of Things (IoT) is a harmonized embedded object and sensor set. It is a
target of intrusions, which leads to considering the security of the IoT environment …

Best of both worlds: Detecting application layer attacks through 802.11 and non-802.11 features

E Chatzoglou, G Kambourakis, C Smiliotopoulos… - Sensors, 2022 - mdpi.com
Intrusion detection in wireless and, more specifically, Wi-Fi networks is lately increasingly
under the spotlight of the research community. However, the literature currently lacks a …

HDFEF: A hierarchical and dynamic feature extraction framework for intrusion detection systems

Y Li, T Qin, Y Huang, J Lan, ZH Liang, T Geng - Computers & Security, 2022 - Elsevier
Network intrusion detection plays a vital role in modern cyberspace security systems.
Although deep learning has been widely used for automatic feature extraction in intrusion …

Fog-assisted deep-learning-empowered intrusion detection system for RPL-based resource-constrained smart industries

D Attique, H Wang, P Wang - Sensors, 2022 - mdpi.com
The Internet of Things (IoT) is a prominent and advanced network communication
technology that has familiarized the world with smart industries. The conveniently acquirable …

EFS‐DNN: An Ensemble Feature Selection‐Based Deep Learning Approach to Network Intrusion Detection System

Z Wang, J Liu, L Sun - Security and Communication Networks, 2022 - Wiley Online Library
In recent years, the scale of networks has substantially evolved due to the rapid
development of infrastructures in real networks. Under the circumstances, intrusion detection …

Deep Learning Approaches for Network Traffic Classification in the Internet of Things (IoT): A Survey

JH Kalwar, S Bhatti - arXiv preprint arXiv:2402.00920, 2024 - arxiv.org
The Internet of Things (IoT) has witnessed unprecedented growth, resulting in a massive
influx of diverse network traffic from interconnected devices. Effectively classifying this …

Adoption of IoT by telecommunication companies in GCC: The role of blockchain

M Alarefi - Decision Science Letters, 2023 - m.growingscience.com
The Internet of Things (IoT) has become essential for business. The adoption rate of IoT has
dropped recently and this could be due to security, privacy, and trust issues. Blockchain (BC) …

Predicting different types of imbalanced intrusion activities based on a multi-stage deep learning approach

R Qaddoura, AZ Ala'M, I Almomani… - 2021 International …, 2021 - ieeexplore.ieee.org
Intrusion Detection Systems for IoT networks have emerged to solve the vulnerabilities
caused by the extensive utilization of IoT devices for different applications. Intrusion …

Mitigating class imbalance for iot network intrusion detection: a survey

JL Leevy, TM Khoshgoftaar… - 2021 IEEE Seventh …, 2021 - ieeexplore.ieee.org
As the number of Internet of Things (IoT) devices continues to rapidly increase, the need to
effectively manage the related security risks has become more obvious. For this reason …