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The Internet of Things (IoT) is a system that connects physical computing devices, sensors, software, and other technologies. Data can be collected, transferred, and exchanged with other devices over the network without requiring human…
The rapid expansion of the Internet of Things (IoT) and its integration with backbone networks have heightened the risk of security breaches. Traditional centralized approaches to anomaly detection, which require transferring large volumes…
Anomaly detection is an important function in IoT applications for finding outliers caused by abnormal events. Anomaly detection sometimes comes with high-frequency data sampling which should be carried out at Edge devices rather than…
With the proliferation of the Internet and smart devices, IoT technology has seen significant advancements and has become an integral component of smart homes, urban security, smart logistics, and other sectors. IoT facilitates real-time…
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover, the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse hardware and software, and being typically placed…
The recent advancements in the Internet of Things (IoT) are giving rise to the proliferation of interconnected devices, enabling various smart applications. These enormous number of IoT devices generates a large capacity of data that…
Since edge device failures (i.e., anomalies) seriously affect the production of industrial products in Industrial IoT (IIoT), accurately and timely detecting anomalies is becoming increasingly important. Furthermore, data collected by the…
The increasing deployment of low-cost IoT sensor platforms in industry boosts the demand for anomaly detection solutions that fulfill two key requirements: minimal configuration effort and easy transferability across equipment. Recent…
Advances in deep neural networks (DNN) greatly bolster real-time detection of anomalous IoT data. However, IoT devices can barely afford complex DNN models due to limited computational power and energy supply. While one can offload anomaly…
IoT systems have been facing increasingly sophisticated technical problems due to the growing complexity of these systems and their fast deployment practices. Consequently, IoT managers have to judiciously detect failures (anomalies) in…
Fog and mobile edge computing (MEC) will play a key role in the upcoming fifth generation (5G) mobile networks to support decentralized applications, data analytics and management into the network itself by using a highly distributed…
Internet of Things (IoT) device localization is fundamental to smart home functionalities, including indoor navigation and tracking of individuals. Traditional localization relies on relative methods utilizing the positions of anchors…
When the equipment is working, real-time collection of environmental sensor data for anomaly detection is one of the key links to prevent industrial process accidents and network attacks and ensure system security. However, under the…
The development and implementation of Internet of Things (IoT) devices have been accelerated dramatically in recent years. As a result, a super-network is required to handle the massive volumes of data collected and transmitted to these…
Anomaly detection is critical in the smart industry for preventing equipment failure, reducing downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large volumes of data from industrial machinery, providing…
IoT devices are increasingly deployed in daily life. Many of these devices are, however, vulnerable due to insecure design, implementation, and configuration. As a result, many networks already have vulnerable IoT devices that are easy to…
Internet of Things (IoT) application providers rely on Mobile Network Operators (MNOs) and roaming infrastructures to deliver their services globally. In this complex ecosystem, where the end-to-end communication path traverses multiple…
The growing number of IoT devices and their use to monitor the operation of machines and equipment increases interest in anomaly detection algorithms running on devices. However, the difficulty is the limitations of the available…
The rapid development in ubiquitous computing has enabled the use of microcontrollers as edge devices. These devices are used to develop truly distributed IoT-based mechanisms where machine learning (ML) models are utilized. However,…
The Internet of Things (IoT), with its high degree of interconnectivity and limited computational resources, is particularly vulnerable to a wide range of cyber threats. Intrusion detection systems (IDS) have been extensively studied to…