Zero-day guardian: A dual model enabled federated learning framework for handling zero-day attacks in 5G enabled IIoT

P Verma, N Bharot, JG Breslin, D O'Shea… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
5G emerges as the bedrock for the Industrial Internet of Things (IIoT), it facilitates the
seamless, low-latency fusion of artificial intelligence and cloud computing, thereby fortifying …

[HTML][HTML] Managing the unknown in machine learning: Definitions, related areas, recent advances, and prospects

M Barcina-Blanco, JL Lobo, P Garcia-Bringas… - Neurocomputing, 2024 - Elsevier
In the rapidly evolving domain of machine learning, the ability to adapt to unforeseen
circumstances and novel data types is of paramount importance. The deployment of Artificial …

Ais-nids: An intelligent and self-sustaining network intrusion detection system

YA Farrukh, S Wali, I Khan, ND Bastian - Computers & Security, 2024 - Elsevier
The ever-evolving landscape of network security is continually molded by the dynamic
evolution of attack vectors and the relentless emergence of new, highly sophisticated …

A hybrid feature selection and aggregation strategy-based stacking ensemble technique for network intrusion detection

Y Huang, G Chen, J Gou, Z Fan, Y Liao - Applied Intelligence, 2025 - Springer
Abstract Intrusion Detection System (IDS) plays an important role in the cybersecurity for
preventing the platform from network attacks. To improve the overall performance of IDS …

[HTML][HTML] A Scalable Approach to Internet of Things and Industrial Internet of Things Security: Evaluating Adaptive Self-Adjusting Memory K-Nearest Neighbor for Zero …

PR Agbedanu, SJ Yang, R Musabe, I Gatare… - Sensors, 2025 - mdpi.com
The Internet of Things (IoT) and Industrial Internet of Things (IIoT) have drastically
transformed industries by enhancing efficiency and flexibility but have also introduced …

ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection

I Khan, YA Farrukh, S Wali - ICC 2024-IEEE International …, 2024 - ieeexplore.ieee.org
In the ever-evolving realm of network security, the swift and accurate identification of diverse
attack classes within network traffic is of paramount importance. This paper introduces …

Towards Novel Malicious Packet Recognition: A Few-Shot Learning Approach

K Stein, AA Mahyari, G Francia… - MILCOM 2024-2024 …, 2024 - ieeexplore.ieee.org
As the complexity and connectivity of networks increase, the need for novel malware
detection approaches becomes imperative. Traditional security defenses are becoming less …

Deep Learning-Based Multiclass Anomaly Detection in the IoT_GPS_Tracker Dataset: Unveiling Patterns for Enhanced Tracking Accuracy

Y Qawqzeh, W Samaraa - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
This paper delves into the utilization of deep learning (DL) techniques for the task of
multiclass anomaly detection within the" IoT_GPS_Tracker" dataset, resulting in an …