A survey on device fingerprinting approach for resource-constraint IoT devices: Comparative study and research challenges

RR Chowdhury, PE Abas - Internet of Things, 2022 - Elsevier
Modernization and technological advancement have made smart and convenient living
environments, including smart houses and smart cities, possible, by combining the Internet …

Overview of AI-models and tools in embedded IIoT applications

P Dini, L Diana, A Elhanashi, S Saponara - Electronics, 2024 - mdpi.com
The integration of Artificial Intelligence (AI) models in Industrial Internet of Things (IIoT)
systems has emerged as a pivotal area of research, offering unprecedented opportunities for …

An efficient deep learning mechanisms for IoT/Non-IoT devices classification and attack detection in SDN-enabled smart environment

P Malini, KR Kavitha - Computers & Security, 2024 - Elsevier
In recent years, the development of Internet of Things (IoT) applications has increased,
resulting in higher demands for sufficient bandwidth, data rates, latency, and quality of …

Marina: Realizing ml-driven real-time network traffic monitoring at terabit scale

M Seufert, K Dietz, N Wehner, S Geißler… - … on Network and …, 2024 - ieeexplore.ieee.org
Network operators require real-time traffic monitoring insights to provide high performance
and security to their customers. It has been shown that artificial intelligence and machine …

Light fidelity for internet of things: A survey

A Petrosino, D Striccoli, O Romanov, G Boggia… - Optical Switching and …, 2023 - Elsevier
Abstract Light-Fidelity (LiFi) is quickly emerging as the next-generation communication
technology thanks to its unique benefits, such as available spectrum, high data rates, low …

Efficient IoT traffic inference: From multi-view classification to progressive monitoring

A Pashamokhtari, G Batista… - ACM Transactions on …, 2023 - dl.acm.org
Machine learning-based techniques have proven to be effective in Internet-of-Things (IoT)
network behavioral inference. Existing works developed data-driven models based on …

Enhancing Cyber Security through Predictive Analytics: Real-Time Threat Detection and Response

M Danish - arxiv preprint arxiv:2407.10864, 2024 - arxiv.org
This research paper aims to examine the applicability of predictive analytics to improve the
real-time identification and response to cyber-attacks. Today, threats in cyberspace have …

Advanced hybrid techniques for cyberattack detection and defense in IoT networks

ZS Mahdi, RM Zaki, L Alzubaidi - Security and Privacy, 2024 - Wiley Online Library
ABSTRACT The Internet of Things (IoT) represents a vast network of devices connected to
the Internet, making it easier for users to connect to modern technology. However, the …

SUTMS: designing a unified threat management system for home networks

A Siddiqui, BP Rimal, M Reisslein, GC Deepak… - IEEE …, 2024 - ieeexplore.ieee.org
The cultural shift of work from on-premises to remote home offices allows hackers to access
corporate data by compromising devices attached to home-based broadband routers …

HSGAN-IoT: A hierarchical semi-supervised generative adversarial networks for IoT device classification

Y **, J Zhou, Y Gao - Computer Networks, 2024 - Elsevier
In recent years, IoT device classification has become a highly focused issue, because it can
achieve network performance optimization, security threat detection, application scenario …