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The ongoing deployment of the Internet of Things (IoT)-based smart applications is spurring the adoption of machine learning as a key technology enabler. To overcome the privacy and overhead challenges of centralized machine learning, there…
The increasing deployment of low-cost industrial IoT (IIoT) sensor platforms on industrial assets enables great opportunities for anomaly classification in industrial plants. The performance of such a classification model depends highly on…
In the age of technology, data is an increasingly important resource. This importance is growing in the field of Artificial Intelligence (AI), where sub fields such as Machine Learning (ML) need more and more data to achieve better results.…
Attacks against the Internet of Things (IoT) are rising as devices, applications, and interactions become more networked and integrated. The increase in cyber-attacks that target IoT networks poses a considerable vulnerability and threat to…
With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and…
The use of lightweight machine learning (ML) models in internet of things (IoT) networks enables resource constrained IoT devices to perform on-device inference for several critical applications. However, the inference accuracy deteriorates…
Security experts have demonstrated numerous risks imposed by Internet of Things (IoT) devices on organizations. Due to the widespread adoption of such devices, their diversity, standardization obstacles, and inherent mobility, organizations…
The generalization of deep learning has helped us, in the past, address challenges such as malware identification and anomaly detection in the network security domain. However, as effective as it is, scarcity of memory and processing power…
The spatiotemporal data generated by massive sensors in the Internet of Things (IoT) is extremely dynamic, heterogeneous, large scale and time-dependent. It poses great challenges (e.g. accuracy, reliability, and stability) in real-time…
For many applications envisioned for the Internet of Things (IoT), it is expected that the sensors will have very low costs and zero power, which can be satisfied by meta-material sensor based IoT, i.e., meta-IoT. As their constituent…
The rapid growth in Internet of Things (IoT) technology has become an integral part of today's industries forming the Industrial IoT (IIoT) initiative, where industries are leveraging IoT to improve communication and connectivity via…
Federated learning (FL) enables wireless terminals to collaboratively learn a shared parameter model while keeping all the training data on devices per se. Parameter sharing consists of synchronous and asynchronous ways: the former…
Nowadays, devices are equipped with advanced sensors with higher processing/computing capabilities. Further, widespread Internet availability enables communication among sensing devices. As a result, vast amounts of data are generated on…
In this paper, we investigate how to deploy computational intelligence and deep learning (DL) in edge-enabled industrial IoT networks. In this system, the IoT devices can collaboratively train a shared model without compromising data…
The Internet of Things (IoT) paradigm has displayed tremendous growth in recent years, resulting in innovations like Industry 4.0 and smart environments that provide improvements to efficiency, management of assets and facilitate…
Various approaches based on supervised or unsupervised machine learning (ML) have been proposed for evaluating IoT data trust. However, assessing their real-world efficacy is hard mainly due to the lack of related publicly-available…
The advent of Large Language Models (LLMs) has profoundly transformed our lives, revolutionizing interactions with AI and lowering the barrier to AI usage. While LLMs are primarily designed for natural language interaction, the extensive…
Federated Learning (FL) has recently become an effective approach for cyberattack detection systems, especially in Internet-of-Things (IoT) networks. By distributing the learning process across IoT gateways, FL can improve learning…
The development and adoption of Internet of Things (IoT) devices will grow significantly in the coming years to enable Industry 4.0. Many forms of IoT devices will be developed and used across industry verticals. However, the euphoria of…
The development of the Internet of Things (IoT) has dramatically expanded our daily lives, playing a pivotal role in the enablement of smart cities, healthcare, and buildings. Emerging technologies, such as IoT, seek to improve the quality…