Privacy-preserving periodical publishing for medical information

Hua Jin; Shi-guang Ju; Shan-cheng Liu

doi:10.1117/12.2031757

19 July 2013 Privacy-preserving periodical publishing for medical information

Hua Jin, Shi-guang Ju, Shan-cheng Liu

Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88780V (2013) https://doi.org/10.1117/12.2031757
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China

Abstract

Existing privacy-preserving publishing models can not meet the requirement of periodical publishing for medical information whether these models are static or dynamic. This paper presents a (k,l)-anonymity model with keeping individual association and a principle based on (Epsilon)-invariance group for subsequent periodical publishing, and then, the PKIA and PSIGI algorithms are designed for them. The proposed methods can reserve more individual association with privacy-preserving and have better publishing quality. Experiments confirm our theoretical results and its practicability.

Citation Download Citation

Hua Jin, Shi-guang Ju, and Shan-cheng Liu "Privacy-preserving periodical publishing for medical information", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88780V (19 July 2013); https://doi.org/10.1117/12.2031757

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