An Improved Fine-Grained Encryption Method for Unstructured Big Data

In the big data protecting technologies, most of the existing data protections adopt entire encryption that leads to the researches of lightweight encryption algorithms, without considering from the protected data itself. In our previous paper (FGEM), it finds that not all the parts of a data need protections, the entire data protection can be supplanted as long as the critical parts of the structured data are protected. Reducing unnecessary encryption makes great sense for raising efficiency in big data processing. In this paper, the improvement of FGEM makes it suitable to protect semi-structured and unstructured data efficiently. By storing semi-structured and unstructured datum in an improved tree structure, the improved FGEM for the datum is achieved by getting congener nodes. The experiments show the improved FGEM has short operating time and low memory consumption.

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