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A survey on intelligent Internet of Things: Applications, security, privacy, and future directions
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …
communication technology and offered various customer services. Artificial intelligence (AI) …
Recent endeavors in machine learning-powered intrusion detection systems for the internet of things
D Manivannan - Journal of Network and Computer Applications, 2024 - Elsevier
The significant advancements in sensors and other resource-constrained devices, capable
of collecting data and communicating wirelessly, are poised to revolutionize numerous …
of collecting data and communicating wirelessly, are poised to revolutionize numerous …
Revolutionizing cyber threat detection with large language models: A privacy-preserving bert-based lightweight model for iot/iiot devices
The field of Natural Language Processing (NLP) is currently undergoing a revolutionary
transformation driven by the power of pre-trained Large Language Models (LLMs) based on …
transformation driven by the power of pre-trained Large Language Models (LLMs) based on …
[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …
reputation for not only building Machine Learning (ML) models that rely on distributed …
[PDF][PDF] Revolutionizing cyber threat detection with large language models
Natural Language Processing (NLP) domain is experiencing a revolution due to the
capabilities of Pre-trained Large Language Models (LLMs), fueled by ground-breaking …
capabilities of Pre-trained Large Language Models (LLMs), fueled by ground-breaking …
Digital twin and federated learning enabled cyberthreat detection system for IoT networks
The widespread deployment of Internet of Things (IoT) devices across various smart city
applications presents significant security challenges, increased by the rapidly evolving …
applications presents significant security challenges, increased by the rapidly evolving …
Federated deep learning for intrusion detection in consumer-centric internet of things
Consumer-centric Internet of Things (CIoT) will play a pivotal role in the fifth industrial
revolution (Industry 5.0) but it exhibits vulnerabilities that can render it susceptible to various …
revolution (Industry 5.0) but it exhibits vulnerabilities that can render it susceptible to various …
[HTML][HTML] Deep neural decision forest (DNDF): A novel approach for enhancing intrusion detection systems in network traffic analysis
Intrusion detection systems, also known as IDSs, are widely regarded as one of the most
essential components of an organization's network security. This is because IDSs serve as …
essential components of an organization's network security. This is because IDSs serve as …
Network intrusion detection and mitigation in SDN using deep learning models
M Maddu, YN Rao - International Journal of Information Security, 2024 - Springer
Abstract Software-Defined Networking (SDN) is a contemporary network strategy utilized
instead of a traditional network structure. It provides significantly more administrative …
instead of a traditional network structure. It provides significantly more administrative …
Deep learning approaches for network traffic classification in the internet of things (iot): A survey
The Internet of Things (IoT) has witnessed unprecedented growth, resulting in a massive
influx of diverse network traffic from interconnected devices. Effectively classifying this …
influx of diverse network traffic from interconnected devices. Effectively classifying this …