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The emergence of the Internet of Things (IoT) technology has caused a powerful transition in the cyber threat landscape. As a result, organisations have had to find new ways to better manage the risks associated with their infrastructure.…

The integration of artificial intelligence (AI) and mobile networks is regarded as one of the most important scenarios for 6G. In 6G, a major objective is to realize the efficient transmission of task-relevant data. Then a key problem…

Cyber-physical systems and the Internet of things (IoT) is becoming an integral part of the digital society. The use of IoT services improves human life in many ways. Protection against cyber threats is an important aspect of the…

Adversarial learning methods have been proposed for a wide range of applications, but the training of adversarial models can be notoriously unstable. Effectively balancing the performance of the generator and discriminator is critical,…

The Internet of Behaviors (IoB) is an emerging concept that utilizes devices to collect human behavior and provide intelligent services. Although some research has focused on human behavior analysis and data collection within IoB, the…

In recent several years, the information bottleneck (IB) principle provides an information-theoretic framework for deep multi-view clustering (MVC) by compressing multi-view observations while preserving the relevant information of multiple…

Variational dimensionality reduction methods are widely used for their accuracy, generative capabilities, and robustness. We introduce a unifying framework that generalizes both such as traditional and state-of-the-art methods. The…

Many of the key enabling technologies of the fifth-generation (5G), such as network slicing, spectrum sharing, and federated learning, rely on a centralized authority. This may lead to pitfalls in terms of security or single point of…

We consider access control for IoT systems that involves shared accesses to the IoT devices as well as their data. Since IoT devices are dispersed all over the edge of the Internet, traditional centralized access control has problems.…

Blockchain, as well as Internet of Things (IoT), is considered as two major disruptive emerging technologies. However, both of them suffer from innate technological limitations to some extent. IoT requires strengthening its security…

Multiview data contain information from multiple modalities and have potentials to provide more comprehensive features for diverse machine learning tasks. A fundamental question in multiview analysis is what is the additional information…

Recently, the Internet of Things (IoT) environment has become increasingly fertile for malicious users to break the security and privacy of IoT users. Access control is a paramount necessity to forestall illicit access. Traditional access…

As Internet of Vehicles (IoV) technology continues to advance, edge computing has become an important tool for assisting vehicles in handling complex tasks. However, the process of offloading tasks to edge servers may expose vehicles to…

In recent years, there has been a growing emphasis on compressing large pre-trained transformer models for resource-constrained devices. However, traditional pruning methods often leave the embedding layer untouched, leading to model…

Blockchain technology has gained increasing popularity in the research of Internet of Things (IoT) systems in the past decade. As a distributed and immutable ledger secured by strong cryptography algorithms, the blockchain brings a new…

The internet of things (IoT) and other emerging ubiquitous technologies are supporting the rapid spread of smart systems, which has underlined the need for safe, open, and decentralized data storage solutions. With its inherent…

Blockchain has received tremendous attention as a secure, distributed, and anonymous framework for the Internet of Things (IoT). As a distributed system, blockchain trades off scalability for distribution, which limits the technologys…

The Internet of Things (IoT) technology will soon become an integral part of our daily lives to facilitate the control and monitoring of processes and objects and revolutionize the ways that human interacts with the physical world. For all…

In the context of statistical learning, the Information Bottleneck method seeks a right balance between accuracy and generalization capability through a suitable tradeoff between compression complexity, measured by minimum description…

In many applications, it is desirable to extract only the relevant information from complex input data, which involves making a decision about which input features are relevant. The information bottleneck method formalizes this as an…