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

Author:

Dong Jingya1234ORCID,Song Chunhe1234ORCID,Zhang Tao1234ORCID,Li Yuanjian25ORCID,Zheng Hao25ORCID

Affiliation:

1. Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China

2. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

3. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China

4. University of Chinese Academy of Sciences, Beijing 100049, China

5. College of Information, Liaoning University, Shenyang 110036, China

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.

Funder

Natural Science Foundation of Liaoning Province

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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