Integration of Edge Computing and Blockchain for Provision of Data Fusion and Secure Big Data Analysis for Internet of Things

【Author】 Dong, Jingya; Song, Chunhe; Zhang, Tao; Li, Yuanjian; Zheng, Hao

【Source】WIRELESS COMMUNICATIONS & MOBILE COMPUTING

【影响因子】2.146

【Abstract】Intelligent computing provides efficient, real-time, and secure data analysis services for the Internet of Things (IoT). As the number of IoT devices increases, IoT generates massive, diverse, and multisourcing datasets that can be used to improve IoT services further. Models trained by intelligent computing from a single system or sensor are often not global, and sending all data directly to the computing platform wastes network bandwidth and may cause network congestion and even privacy leakage. To ensure IoT applications' quality of service and privacy, we propose a framework that integrates edge computing and blockchain to provide lightweight data fusion and secure data analysis for IoT. We propose a lightweight data fusion method that can reduce the amount of data at the node level and prevent network congestion and bandwidth waste. Furthermore, we propose a hierarchical fuzzy hashing method to check and locate anomalies of IoT machine learning models to ensure the validity of IoT intelligent computing and the security of sensitive data. Finally, we demonstrate the effectiveness of the method proposed in this paper through experiments.

【Keywords】

【发表时间】2022 MAY 18

【收录时间】2022-06-12

【文献类型】实证性文章

【主题类别】

区块链技术-协同技术-边缘计算