A Blockchain-Based Access Control Framework for Cyber-Physical-Social System Big Data

Liang Tan,Caixia Yang,Na Shi,Keping Yu

doi:10.1109/access.2020.2988951

Abstract

Cyber-Physical-Social System (CPSS) big data is specified as the global historical data which is usually stored in cloud, the local real-time data which is usually stored in the fog-edge server (FeS) of the mobile terminal devices or sensors, and the social data which is usually stored in the social data server (SdS), moreover adopts a centralized access control mechanism to offer users' access strategy which can easily cause CPSS big data to be tampered with and to be leaked. Therefore, a blockchain-based access control scheme called BacCPSS for CPSS big data is proposed. In BacCPSS, account address of the node in blockchain is used as the identity to access CPSS big data, the access control permission for CPSS big data is redefined and stored in blockchain, and processes of authorization, authorization revocation, access control and audit in BacCPSS are designed, and then a lightweight symmetric encryption algorithm is used to achieve privacy-preserving. Finally, a credible experimental model on EOS and Aliyun cloud is built. Results show that BacCPSS is feasible and effective, and can achieve secure access in CPSS while protecting privacy.

Highlights

Cyber-Physical-Social System (CPSS) [1]–[3] integrates the cyber, physical and social spaces together
We propose an access control scheme called BacCPSS for CPSS that is based on the blockchain [17]– [19] which has the characteristics of decentralization, without tampering and trustworthiness
WORK It is an important research direction to solve the security of access control in CPSS big data by utilizing the features of blockchain

Summary

INTRODUCTION

Cyber-Physical-Social System (CPSS) [1]–[3] integrates the cyber, physical and social spaces together. The security and privacy issues of CPSS big data [15] have been widely concerned [16], the access right in authorization database of cloud platform, fog-edge server and social server is being tampered by administrator or attackers, this centralized management method is prone to lead to disclose CPSS big data. 3) Establish an experimental model on EOS and Alibaba Cloud, and prove the effectiveness of BacCPSS by evaluating the three indicators of defined computation overhead, storage overhead, and throughput.

BACKGROUND

SECURITY AND FEATURE ANALYSIS

CONCLUSION AND FUTURE WORK