Optimize Parallel Data Access in Big Data Processing

Author(s):  
Jiangling Yin ◽  
Jun Wang
2018 ◽  
Vol 173 ◽  
pp. 03047
Author(s):  
Zhao Li ◽  
Shuiyuan Huan

There are many security threats such as data’s confidentiality and privacy protection in the new application scenario of big data processing, and for the problems such as coarse granularity and low sharing capability existing in the current research on big data access control, a new model to support fine-grained access control and flexible attribute change is proposed. Based on CP-ABE method, a multi-level attribute-based encryption scheme is designed to solve fine-grained access control problem. And to solve the problem of attribute revocation, the technique of re-encryption and version number tag is integrated into the scheme. The analysis shows that the proposed scheme can meet the security requirement of access control in big data processing environment, and has an advantage in computational overhead compared with the previous schemes.


2019 ◽  
Vol 12 (1) ◽  
pp. 42 ◽  
Author(s):  
Andrey I. Vlasov ◽  
Konstantin A. Muraviev ◽  
Alexandra A. Prudius ◽  
Demid A. Uzenkov

Sign in / Sign up

Export Citation Format

Share Document