Issue |
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|
|
---|---|---|
Article Number | 03018 | |
Number of page(s) | 5 | |
Section | Smart Algorithms and Recognition | |
DOI | https://doi.org/10.1051/matecconf/202030903018 | |
Published online | 04 March 2020 |
Information exposure rating based on hierarchical model for big data
1 School of Mathematics and Computer, Hezhou University, Hezhou Guangxi 542899, China
2 Audit Division, Zunyi Normal College, Zunyi Guizhou 563006, China
* Corresponding author: 2055164364@qq.com
Big data improves the function of information, but also increases the exposure of information leakage. From the perspective of information leakage, Information entropy is used to quantify information, and the quantitative index of security exposure are identified as mutual information, and a hierarchical exposure assessment model is established. With the help of local priority principle, classify the types of information leaks and attack methods, the mutual information is determined as quantitative indicators for the exposure of information disclosure. The security exposure of information leakage is evaluated by fuzzy comprehensive evaluation
Key words: Information / Exposure information / Exposure quantification / Hierarchical
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.