Abstract
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.
Highlights
Nowadays, the society is in a big data era of large-scale production, sharing and application of data, big data analysis and processing technologies are widely used in all walks of life
A typical enterprise big data application scenario is as follows: diversified data are gathered from multiple service channels to the enterprise big data processing platform for processing and analysis, the analysis results will be used by enterprise subordinate organizations or business departments according to their business needs
It still needs to be comprehensively considered in the following aspects: 1) Because of its complexity, ABE is not suitable for encryption of large-scale data, it should be improved to adapt to the data size and the growth rate in big data application scenarios; 2) Big data applications are quite complex for data collection, storage, sharing, and utilization, these steps are quite time-consuming, so the repeated processing of data should be avoided in big data access control scheme; 3) In the big data application scenario, it is generally necessary to set up a large set of attributes to achieve fine-grained access control, so how to realize flexible and efficient attribute revocation in big data access control scheme is an important issue
Summary
The society is in a big data era of large-scale production, sharing and application of data, big data analysis and processing technologies are widely used in all walks of life. Attribute-based encryption (ABE) scheme enables secure, fine-grained access control, which provides a way to achieve access control for big data. It still needs to be comprehensively considered in the following aspects: 1) Because of its complexity, ABE is not suitable for encryption of large-scale data, it should be improved to adapt to the data size and the growth rate in big data application scenarios; 2) Big data applications are quite complex for data collection, storage, sharing, and utilization, these steps are quite time-consuming, so the repeated processing of data should be avoided in big data access control scheme; 3) In the big data application scenario, it is generally necessary to set up a large set of attributes to achieve fine-grained access control, so how to realize flexible and efficient attribute revocation in big data access control scheme is an important issue. This paper presents a multi-level access control scheme based on ciphertext-policy attribute-based encryption (CP-ABE) scheme, which can realize secure and flexible access control in big data environment
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