Along with the rapid development of cloud computing, IoT, and AI technologies, video surveillance (CVS) has become a hotly discussed topic, especially when facing requirement real-time analysis in smart applications. Object detection usually plays an important role for environment monitoring activity tracking system. The emerging edge-cloud computing paradigm provides us opportunity to deal continuously generated huge amount data on-site manner across IoT systems. However, performance is...

Abstract Background The COVID-19 pandemic has become a great threat to public health, which greatly impacted the study and life of undergraduate students in China. This aims perform survey their knowledge, attitude practice (KAP) associated with COVID-19. Methods A cross-sectional was designed gather information regarding related KAP among undergraduates during home isolation outbreak. Subjects were recruited from 10 universities Shaanxi Province, Enrollees voluntarily submitted answers...

In order to overcome the difficulty of password management and improve usability authentication systems, biometric has been widely studied attracted special attention in both academia industry. Many systems have researched developed, especially for mobile devices. However, existing still defects. Some biological features not deeply investigated. The could be vulnerable attacks, such as replay attack suffer from user privacy intrusion, which seriously hinder their wide acceptance by end...

Deep learning, as the most important architecture of current computational intelligence, achieves super performance to predict cloud workload for industry informatics. However, it is a nontrivial task train deep learning model efficiently since often includes great number parameters. In this paper, an efficient based on canonical polyadic decomposition proposed model, parameters are compressed significantly by converting weight matrices format. Furthermore, algorithm designed Finally,...

The vision of the upcoming 6G technologies that have fast data rate, low latency, and ultra-dense network, draws great attentions to Internet Vehicles (IoV) Vehicle-to-Everything (V2X) communication for intelligent transportation systems. There is an urgent need distributed machine learning techniques can take advantages massive interconnected networks with explosive amount heterogeneous generated at network edge. In this study, a two-layer federated model proposed end-edge-cloud...

Internet of Things (IoT) is gaining increasing popularity. Overwhelming volumes data are generated by IoT devices. Those after analytics provide significant information that could greatly benefit applications. Different from traditional applications, such as environmental monitoring, smart navigation, and healthcare come with new requirements, mobility, real-time response, location awareness. However, cloud computing paradigm cannot satisfy these demands due to centralized processing being...

Permissionless blockchain, as a kind of distributed ledger, has gained considerable attention because its openness, transparency, decentralization, and immutability. Currently, permissionless blockchain shown good application prospect in many fields, from the initial cryptocurrency to Internet Things (IoT) Vehicular Ad-Hoc Networking (VANET), which is considered beginning rewriting our digital infrastructure. However, confronts some privacy risks that hinder practical applications. Though...

Smart manufacturing aims to support highly customizable production processes. Therefore, the associated machine intelligence needs be quickly adaptable new products, processes, and applications with limited training data while preserving privacy. In this article, a federated transfer learning framework, for cross-domain prediction, is proposed address challenges of scarcity privacy faced by most approaches in modern smart applications. The framework architecture consists central server...

Traffic classification groups similar or related traffic data, which is one main stream technique of data fusion in the field network management and security. With rapid growth users emergence new networking services, has attracted increasing attention. Many techniques have been developed widely applied. However, existing literature lacks a thorough survey to summarize, compare analyze recent advances order deliver holistic perspective. This paper carefully reviews methods from comprehensive...

The proliferation in embedded and communication technologies made the concept of Internet Medical Things (IoMT) a reality. Individuals' physical physiological status can be constantly monitored, numerous data collected through wearable mobile devices. However, silo individual brings limitations to existing machine learning approaches correctly identify user's health status. Distributed paradigms, such as federated learning, offer potential solution for privacy-preserving knowledge sharing...

Swarms of mobile robots are being widely applied for complex tasks in various practical scenarios toward modern smart industry. Federated learning (FL) has been developed as a promising privacy-preserving paradigm to tackle distributed machine robotic systems 5G and beyond networks. However, unstable wireless network conditions the harsh working environment may lead poor communication quality bring big challenges traditional centralized global training FL models. In this article,...

The high-speed mobile networks offer great potentials to many future intelligent applications, such as autonomous vehicles in smart transportation systems. Such provide the possibility interconnect devices achieve fast knowledge sharing for efficient collaborative learning and operations, especially with help of distributed machine learning, e.g., Federated Learning (FL), modern digital technologies, Digital Twin (DT) Typically, FL requires a fixed group participants that have Independent...

The proliferation of the Internet Things (IoT), wearable computing, and social media technologies bring forward realization so-called Cyber-Physical-Social Systems (CPSS), which is capable offering intelligent services in many different aspects our day-to-day life. While CPSS offer a wide variety data from devices, challenges such as silos secure sharing still remain. In this study, 2-Dimensional Federated Learning (2DFL) framework, including vertical horizontal federated learning phases,...

Internet of Things (IoT) aims to create a vast network with billions things that can seamlessly and exchange data, establishing intelligent interactions between people objects around them. It is characterized openness, heterogeneity, dynamicity, which inevitably introduce severe security, privacy, trust issues hinder the widespread application IoT. Trust management (TM) holds great promise in identifying malicious nodes, maintaining relationships, enhancing system security. Traditional TM...

Wireless sensor network (WSN) is an indispensible part of Internet Things that has been applied in many fields to monitor environments and collect data from surroundings. However, WSNs are highly susceptible attacks due its unique characteristics: large-scale, self-organization, dynamic topology, constrained resources. A number systems have proposed effectively detect varieties WSNs. most previous surveys on WSN focus detection methods for only one or two types lack detailed performance...

Cloud computing offers a new way of service provision by re-arranging various resources over the Internet. The most important and popular cloud is data storage. In order to preserve privacy holders, are often stored in an encrypted form. However, introduce challenges for deduplication, which becomes crucial big storage processing cloud. Traditional deduplication schemes cannot work on data. Existing solutions suffer from security weakness. They flexibly support access control revocation....

With the great success of second-generation wireless telephone technology and third-generation mobile telecommunications technology, fast development fourth-generation phase fifth-generation networks or systems 5G is coming. In this article, we indicate open research issues security trust in context virtualized networking software-defined networking. We further propose a framework focusing on solving network issues. The proposed applies adaptive evaluation management technologies sustainable...

Cloud computing offers a new way of services and has become popular service platform. Storing user data at cloud center greatly releases storage burden devices brings access convenience. Due to distrust in providers, users generally store their crucial an encrypted form. But many cases, the need be accessed by other entities for fulfilling expected service, e.g., eHealth service. How control personal is critical issue. Various application scenarios request flexible on based owner policies...