Malicious Participants and Fake Task Detection Incorporating Gaussian Bias
Mobile crowdsensing (MCS) is a combination of crowdsourcing ideas and mobile sensing devices, designed to enable rational allocation of resources at scale. However, the MCS platform is highly vulnerable to injection attacks from malicious participants and ...
Conscious Task Recommendation via Cognitive Reasoning Computing in Mobile Crowd Sensing
Mobile Crowd Sensing is a human-based data collection model, and the approach taken to recommend data collection tasks to users in order to maximize task acceptance rates is an important part of this research. Existing task recommendation methods are ...
RFL-LSU: A Robust Federated Learning Approach with Localized Stepwise Updates
Distributed intelligence enables the widespread deployment of AI technology, greatly promoting the development of AI. Federated learning is a widely used distributed intelligence technology that allows iterative optimization of global model while ...
Local Load Migration in High-Capacity Fog Computing
Fog computing brings storage and computational capabilities closer to the data source, which reduces latency and enhances efficiency in processing data. However, these capabilities are resource-constrained at the fog nodes as compared to the cloud core. ...
Exposing Stealthy Wash Trading on Automated Market Maker Exchanges
Decentralized Finance (DeFi), a pivotal component of the emerging Web3 landscape, is gaining popularity but remains vulnerable to market manipulations, such as wash trading. Wash trading is an illegal practice, where traders buy and sell assets to ...
Model-Driven Development Towards Distributed Intelligent Systems
A Distributed Intelligent System (DIS) encompasses a set of intelligent subsystems and components that collaborate to perform tasks and solve problems. Given the advancements of paradigms such as the Internet of Things, along with the advancements of ...
Adaptive Compression-Aware Split Learning and Inference for Enhanced Network Efficiency
The growing number of AI-driven applications in mobile devices has led to solutions that integrate deep learning models with the available edge-cloud resources. Due to multiple benefits such as reduction in on-device energy consumption, improved latency, ...
Towards a Sustainable Blockchain: A Peer-to-Peer Federated Learning based Approach
In the rapidly evolving digital world, blockchain technology is becoming the foundation for numerous applications, ranging from financial services to supply chain management. As the usage of blockchain is becoming more prevalent, the energy-intensive ...
Navigating the Metaverse: A Comprehensive Analysis of Consumer Electronics Prospects and Challenges
Rapid innovation in consumer electronics has made our lives more comfortable. Consumer electronics serve as the primary platform for the Metaverse (MV), offering users an immersive and interactive medium that connects the digital and real worlds. Consumer ...
A Novel Point Cloud Registration Method for Multimedia Communication in Automated Driving Metaverse
The development of the Metaverse offers more possibilities for autonomous driving. This is mainly reflected in the fact that the scene reconstructed based on multiple sensors can help the autonomous vehicle establish a Metaverse world based on its own ...
A New Layer Structure of Cyber-Physical Systems under the Era of Digital Twin
Cyber-Physical Systems (CPS) are new systems designed to support and synthesize sensing, communication, and computing components that interact with physical objects so that the system can sense, monitor, control, and respond to changes occurring in their ...
DeGONet: Decentralized Group-Oriented Interconnection Network for IoT-enabled Metaverse
As a transformative technology across various industries, the metaverse has emerged to connect the physical world with the virtual world. During this process, the Internet of Things (IoT) has played a critical role in achieving effective cyber-physical ...
FedGK: Communication-Efficient Federated Learning through Group-Guided Knowledge Distillation
Federated learning (FL) empowers a cohort of participating devices to contribute collaboratively to a global neural network model, ensuring that their training data remains private and stored locally. Despite its advantages in computational efficiency and ...
LSDN Empowers the Metaverse Communication to Achieve High-Resolution Visuals with Lower Bandwidth
Deploying super-resolution models on metaverse terminal devices can enhance visual effects without increasing network bandwidth. However, deploying most current super-resolution networks on metaverse terminal devices with limited hardware resources poses ...
Interpersonal Communication Interconnection in Media Convergence Metaverse
The metaverse aims to provide immersive virtual worlds connecting with the physical world. To enable real-time interpersonal communications between users across the globe, the metaverse places high demands on network performance, including low latency, ...
Data management for continuous learning in EHR systems
To gain a comprehensive understanding of a patient’s health, advanced analytics must be applied to the data collected by electronic health record (EHR) systems. However, managing and curating this data requires carefully designed workflows. While ...
Multi-Think Transformer for Enhancing Emotional Health
The smart healthcare system not only focuses on physical health but also on emotional health. Music therapy, as a non-pharmacological treatment method, has been widely used in clinical treatment, but music selection and generation still require manual ...
Audio-Visual Event Localization using Multi-task Hybrid Attention Networks for Smart Healthcare Systems
Human perception heavily relies on two primary senses: vision and hearing, which are closely inter-connected and capable of complementing each other. Consequently, various multimodal learning tasks have emerged, with audio-visual event localization (AVEL) ...
AI-assisted Blockchain-enabled Smart and Secure E-prescription Management Framework
Traditional medical prescriptions based on physical paper-based documents are prone to manipulation, errors, and unauthorized reproduction due to their format. Addressing the limitations of the traditional prescription system, e-prescription systems have ...
Atrial Fibrillation Detection from Compressed ECG Measurements for Wireless Body Sensor Network
Recent years have witnessed an increasing prevalence of wearable devices in the public, where atrial fibrillation (AF) detection is a popular application in these devices. Generally, AF detection is performed on cloud whereas this paper describes an on-...
Federated Learning-based Information Leakage Risk Detection for Secure Medical Internet of Things
The Medical Internet of Things (MIoT) requires extreme information and communication security, particularly for remote consultation systems. MIoT’s integration of physical and computational components creates a seamless network of medical devices ...
ML-Based Identification of Neuromuscular Disorder Using EMG Signals for Emotional Health Application
Abstract: The electromyogram (EMG), also known as an EMG, is used to assess nerve impulses in motor nerves, sensory nerves, and muscles. EMS is a versatile tool used in various biomedical applications. It is commonly employed to determine physical health, ...
An IoT and Deep Learning-Based Smart Healthcare Framework for Thyroid Cancer Detection
A world of healthcare possibilities has been opened with the development of the Internet of Medical Things and related machine learning, deep learning, and artificial intelligence approaches. It has a broad range of uses: when linked to the Internet, ...
A Softwarized Intrusion Detection System for IoT-Enabled Smart Healthcare System
The Internet of Things-enabled Smart Healthcare System (IoT-SHS) is a networked infrastructure of intelligent wearables, software applications, health systems, and services that continuously monitors and transmits patient-sensitive data using an open ...