Related Experiment Videos
Edge Computing and Blockchain for Quick Fake News Detection in IoV
Yonggang Xiao1, Yanbing Liu1, Tun Li1
1School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Abstract:
The dissemination of false messages in Internet of Vehicles (IoV) has a negative impact on road safety and traffic efficiency. Therefore, it is critical to quickly detect fake news considering news timeliness in IoV. We propose a network computing framework Quick Fake News Detection (QcFND) in this paper, which exploits the technologies from Software-Defined Networking (SDN), edge computing, blockchain, and Bayesian networks. QcFND consists of two tiers: edge and vehicles. The edge is composed of Software-Defined Road Side Units (SDRSUs), which is extended from traditional Road Side Units (RSUs) and hosts virtual machines such as SDN controllers and blockchain servers. The SDN controllers help to implement the load balancing on IoV. The blockchain servers accommodate the reports submitted by vehicles and calculate the probability of the presence of a traffic event, providing time-sensitive services to the passing vehicles. Specifically, we exploit Bayesian Network to infer whether to trust the received traffic reports. We test the performance of QcFND with three platforms, i.e., Veins, Hyperledger Fabric, and Netica. Extensive simulations and experiments show that QcFND achieves good performance compared with other solutions.
Related Concept Videos
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Distribution Reliability and Automation
Non-equilibrium in the Cell
Biasing of FET
In an N-channel JFET, the structure consists of N-type material forming the channel on a P-type substrate, with the...
Rolling Resistance: Problem Solving
Distributed Loads: Problem Solving