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A survey on device fingerprinting approach for resource-constraint IoT devices: Comparative study and research challenges
Modernization and technological advancement have made smart and convenient living
environments, including smart houses and smart cities, possible, by combining the Internet …
environments, including smart houses and smart cities, possible, by combining the Internet …
Overview of AI-models and tools in embedded IIoT applications
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 …
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
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 …
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
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 …
and security to their customers. It has been shown that artificial intelligence and machine …
Light fidelity for internet of things: A survey
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 …
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
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 …
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 …
real-time identification and response to cyber-attacks. Today, threats in cyberspace have …
Advanced hybrid techniques for cyberattack detection and defense in IoT networks
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 …
the Internet, making it easier for users to connect to modern technology. However, the …
SUTMS: designing a unified threat management system for home networks
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 …
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 …
achieve network performance optimization, security threat detection, application scenario …