A holistic review of machine learning adversarial attacks in IoT networks

H Khazane, M Ridouani, F Salahdine, N Kaabouch - Future Internet, 2024 - mdpi.com
With the rapid advancements and notable achievements across various application
domains, Machine Learning (ML) has become a vital element within the Internet of Things …

Survey on Unified Threat Management (UTM) Systems for Home Networks

A Siddiqui, BP Rimal, M Reisslein… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Home networks increasingly support important networked applications with limited
professional network administration support, while sophisticated attacks pose enormous …

A novel deep learning-based intrusion detection system for IoT DDoS security

S Hizal, U Cavusoglu, D Akgun - Internet of Things, 2024 - Elsevier
Intrusion detection systems (IDS) for IoT devices are critical for protecting against a wide
range of possible attacks when dealing with Distributed Denial of Service (DDoS) attacks …

Netdiffusion: Network data augmentation through protocol-constrained traffic generation

X Jiang, S Liu, A Gember-Jacobson… - Proceedings of the …, 2024 - dl.acm.org
Datasets of labeled network traces are essential for a multitude of machine learning (ML)
tasks in networking, yet their availability is hindered by privacy and maintenance concerns …

Predictive video analytics in online courses: A systematic literature review

OR Yürüm, T Taşkaya-Temizel, S Yıldırım - Technology, Knowledge and …, 2024 - Springer
The purpose of this study was to investigate the use of predictive video analytics in online
courses in the literature. A systematic literature review was performed based on a hybrid …

Attribute-Based Bilateral Access Control With Sanitization and Trust Management for IIoT

Z Wang, Y Fu, X Lin - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
The Industrialindustrial IoT (IIoT) is an important cornerstone to realize the fourth industrial
revolution. Data sharing is one of the key elements of IIoT, and cloud-edge-device …

[HTML][HTML] A comparative evaluation of intrusion detection systems on the edge-IIoT-2022 dataset

T Al Nuaimi, S Al Zaabi, M Alyilieli, M AlMaskari… - Intelligent Systems with …, 2023 - Elsevier
We propose and evaluate a data-driven intrusion detection system (IDS) for the Internet of
Things (IoT) and Industrial IoT (IIoT) environments using the Edge-IIoT-2022 dataset. We …

[HTML][HTML] Extraction of Minimal Set of Traffic Features Using Ensemble of Classifiers and Rank Aggregation for Network Intrusion Detection Systems

J Krupski, M Iwanowski, W Graniszewski - Applied Sciences, 2024 - mdpi.com
Network traffic classification models, an essential part of intrusion detection systems, need to
be as simple as possible due to the high speed of network transmission. One of the fastest …

GothX: a generator of customizable, legitimate and malicious IoT network traffic

M Poisson, R Carnier, K Fukuda - Proceedings of the 17th Cyber …, 2024 - dl.acm.org
In recent years, machine learning-based anomaly detection (AD) has become an important
measure against security threats from Internet of Things (IoT) networks. Machine learning …

Enhancing IoT security: Assessing instantaneous communication trust to detect man-in-the-middle attacks

R Basri, G Karmakar, SHS Newaz… - Future Generation …, 2025 - Elsevier
Communication trust is regarded as an effective tool to detect various dangerous cyber
attacks, including Man-in-the-Middle (MITM) attacks and acts as a complement to zero trust …