In digital societies, users’ privacy decisions not only affect personal information security and application sustainability, but also profoundly influence the formulation and enforcement of relevant laws. However, existing research mainly adopt...
Participatory sensing is a process whereby mobile device users (or participants) collect environmental data on behalf of a service provider who can then build a service based upon these data. To attract submissions of such data, the service provider...
Crowdsensing systems have been developed for wide-area sensing tasks because humancarried smartphones are prevailing and becoming capable. To encourage more people to participate in sensing tasks, various incentive mechanisms were proposed. However,...
25 September 2023
In the era of digital healthcare, biomedical data sharing is of paramount importance for the advancement of research and personalised healthcare. However, sharing such data while preserving user privacy and ensuring data security poses significant ch...
Location-based services (LBS) bring convenience to people’s lives but are also accompanied with privacy leakages. To protect the privacy of LBS users, many location privacy protection algorithms were proposed. However, these algorithms often ha...
To address the issues of privacy-utility imbalance, insufficient incentives, and lack of verifiable computation in current medical data sharing, this paper proposes a blockchain-based fair verification and adaptive differential privacy mechanism. The...
The rapid proliferation of handheld intelligent devices and the advent of 5G technology have brought about convenient and fast services for people. In perception-oriented application services, participating users will upload sensitive mobile data in...
In order to solve the problem that data of the industrial Internet of Things (IIoT) is easily tampered with and therefore, the authenticity of data may be questioned, a data-privacy security mechanism of the IIoT based on blockchain is proposed. At t...
Crowd sensing is a perception mode that recruits mobile device users to complete tasks such as data collection and cloud computing. For the cloud computing platform, crowd sensing can not only enable users to collaborate to complete large-scale aware...
Reporting helps to combat illegal activities and deters lawbreakers and potential lawbreakers. From ancient times to the present, public authorities have usually rewarded effective reporting information to build harmonious societies. In this process,...
With the advent of the digital age, traditional lifestyle activities, such as reading books, referencing recipes, and enjoying music, have progressively transitioned from offline to online. However, numerous issues plague the conventional approach to...
Due to the increasing relevance of spatial information in different aspects of location-based services, various methods are used to collect this information. The use of crowdsourcing due to plurality and distribution is a remarkable strategy for coll...
Reinforcement learning is a machine learning framework that relies on a lot of trial-and-error processes to learn the best policy to maximize the cumulative reward through the interaction between the agent and the environment. In the actual use of th...
Federated learning enables privacy-preserving model training across distributed clients, yet real-world deployments face statistical, system, and behavioral heterogeneity, which degrades performance and increases vulnerability to adversarial clients....
With the rapid development of artificial intelligence (AI) in the healthcare industry, the sharing of personal healthcare data plays an essential role in advancing medical AI. Unfortunately, personal healthcare data sharing is plagued by challenges l...
Climate change is a global priority. In 2015, the United Nations (UN) outlined its Sustainable Development Goals (SDGs), which stated that taking urgent action to tackle climate change and its impacts was a key priority. The 2021 World Climate Summit...
As the realization of fully autonomous driving becomes increasingly plausible, its rapid development raises serious privacy concerns. At present, while personal information of passengers and pedestrians is routinely collected, its purpose and usage h...
The Chinese social credit system (SCS) is a digital sociotechnical credit system that rewards and sanctions the economic and social behaviors of individuals and companies. This article uses classic social-control theories—the shaming theory and...
Federated Learning (FL), a key paradigm in privacy-preserving and distributed machine learning (ML), enables collaborative model training across decentralized data sources without requiring raw data exchange. FL enables collaborative model training a...
Federated learning enables multiple users to collaboratively train a global model using the users’ private data on users’ local machines. This way, users are not required to share their training data with other parties, maintaining user p...
Because of the rise of cryptocurrencies and decentralized apps, blockchain technology has generated a lot of interest. Among these is the emergent blockchain-based crowdsourcing paradigm, which eliminates the centralized conventional mechanism server...
In recent years, many mobile edge computing network solutions have enhanced data privacy and security and built a trusted network mechanism by introducing blockchain technology. However, this also complicates the task-offloading problem of blockchain...
As the medical information systems continue to develop, the sharing of electronic medical records (EMRs) is becoming a vital tool for improving the quality and efficiency of medical services. However, during the process of sharing EMRs, establishing...
With the rapid advancement of intelligent transportation systems (ITSs), behavior detection within the Internet of Vehicles (IoVs) has become increasingly critical for maintaining system security and operational stability. However, existing detection...
In network function virtualization (NFV) environments, dynamic network traffic prediction with unique symmetric and asymmetric traffic patterns is critical for efficient resource orchestration and service chain optimization. Traditional centralized p...
Federated Learning (FL) enables privacy-preserving model training across distributed clients. However, its reliance on voluntary client participation makes it vulnerable to strategic behaviors—actions that are not overtly malicious but signific...
With the deployment of fifth-generation (5G) mobile communication technology and rapid advancements in artificial intelligence and edge computing, smart construction sites have emerged as a critical direction for the construction industry’s tra...
In recent years, self-autonomous intelligent transportation applications such as drones and autonomous vehicles have seen rapid development and deployment across various countries. Within the domain of artificial intelligence, self-autonomous agents...
To build intelligent model learning in conventional architecture, the local data are required to be transmitted toward the cloud server, which causes heavy backhaul congestion, leakage of personalization, and insufficient use of network resources. To...
Residential microgrid is widely considered as a new paradigm of the home energy management system. The complexity of Microgrid Energy Scheduling (MES) is increasing with the integration of Electric Vehicles (EVs) and Renewable Generations (RGs). More...
Currently, the concept of Mobile Edge Computing (MEC) has been applied as a solution against the plethora of demands for high-quality computing services. It comprises several essential processes, such as resource allocation, data transmission, and ta...
The emergence of the Internet of Vehicles (IoV) aims to facilitate the next generation of intelligent transportation system (ITS) applications by combining smart vehicles and the internet to improve traffic safety and efficiency. On the other hand, m...
Industrial Internet of Things (IIoT) systems are enhancing the delivery of services and boosting productivity in a wide array of industries, from manufacturing to healthcare. However, IIoT devices are susceptible to cyber-threats such as the leaking...
Federated learning has won a lot of interest in recent years, due to its capability in collaborative learning and privacy preservation. To ensure the accuracy of outsourced training tasks, task publishers prefer to assign tasks to task workers with a...
A central authority, in a conventional centralized energy trading market, superintends energy and financial transactions. The central authority manages and controls transparent energy trading between producer and consumer, imposes a penalty in case o...
With the growing adoption of circular economy principles in manufacturing, efficient disassembly and reassembly of end-of-life (EOL) products has become a key challenge in smart factories. This paper addresses the Disassembly and Assembly Line Balanc...