Quantitative Robust Declassification

Authors

Hao Zhu, School of Computer Science and Technology, Nantong University, Nantong, 226019, P. R. China\\ School of Computer Science and Technology, Nanjing University of Aeronautics Astronautics, Nanjing, 210016, P. R. ChinaFollow
Yi Zhuang
Xiang Chen

Author Country (or Countries)

P. R. China

Abstract

The previous declassification policies focus on qualitative analysis of security properties along different dimensions, lacking quantitative analysis of them. As a step in this direction, we relax restrictiveness of robustness of declassification from the quantitative aspect, and propose a definition of robustness rate of declassification, based on Shannon’s measure method of information lattice. We show our definition is equivalent to robust declassification when the value of robustness rate is equal to 1. Moreover, we make a theoretical and experimental analysis of robust rate about the laundering attack on average salary, respectively. The experimental results are consistent with the theoretical results completely.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.12785/amis/080464

Recommended Citation

Zhu, Hao; Zhuang, Yi; and Chen, Xiang (2014) "Quantitative Robust Declassification," Applied Mathematics & Information Sciences: Vol. 08: Iss. 4, Article 64.
DOI: http://dx.doi.org/10.12785/amis/080464
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss4/64