A Privacy-Preserving Health Data Aggregation Scheme = A Privacy-Preserving Health Data Aggregation Scheme

다국어 초록 (Multilingual Abstract)

Patients` health data is very sensitive and the access to individual`s health data should be strictly restricted. However, many data consumers may need to use the aggregated health data. For example, the insurance companies needs to use this data to setup the premium level for health insurances. Therefore, privacy-preserving data aggregation solutions for health data have both theoretical importance and application potentials. In this paper, we propose a privacy-preserving health data aggregation scheme using differential privacy. In our scheme, patients` health data are aggregated by the local healthcare center before it is used by data comsumers, and this prevents individual`s data from being leaked. Moreover, compared with the existing schemes in the literature, our work enjoys two additional benefits: 1) it not only resists many well known attacks in the open wireless networks, but also achieves the resilience against the human-factor-aware differential aggregation attack; 2) no trusted third party is employed in our proposed scheme, hence it achieves the robustness property and it does not suffer the single point failure problem.

참고문헌 (Reference)

1 D. Boneh., "Short signatures from the Weil pairing" 514 (514): 514-532, 2001

2 C. Hu., "Securing communications between external users and wireless body area networks" 31-36, 2013

3 D. He., "Secure and lightweight network admission and transmission protocol for body sensor networks" 17 (17): 664-674, 2013

4 D. He., "Privacy-preserving data aggregation scheme against internal attackers in smart grids" 22 (22): 491-502, 2016

5 C. I. Fan., "Privacy-enhanced data aggregation scheme against internal attackers in smart grid" 10 (10): 666-675, 2014

6 K. Zhang., "PHDA : A priority based health data aggregation with privacy preservation for cloud assisted WBANs" 284 : 130-141, 2014

7 D. Cynthia., "Our data, ourselves : privacy via distributed noise generation" 486-503, 2006

8 H. Y. Lin, "On the security of a dynamic ID-based authentication scheme for telecare medical information systems" 37 (37): 1-5, 2013

9 J. M. Pollard, "Monte carlo methods for index computation(mod p)" 32 (32): 918-924, 1978

10 T. Cao., "Improved dynamic ID-based authentication scheme for telecare medical information systems" 37 (37): 1-7, 2013

11 Zheng Yuhui., "Image segmentation by generalized hierarchical fuzzy C-means algorithm" 28 (28): 961-973, 2015

12 W. Jia., "Human-factor-aware privacy-preserving aggregation in smart grid" 8 (8): 598-607, 2014

13 D. Boneh., "Evaluating 2-DNF formulas on ciphertexts" 325-341, 2005

14 Jian Shen, "Enhanced Secure Sensor Association and Key Management in Wireless Body Area Networks" 한국통신학회 17 (17): 453-462, 2015

15 J. Shao, "Efficient verifiable multi-secret sharing scheme based on hash function" 278 : 104-109, 2014

16 H. Li., "EPPDR : An efficient privacy-preserving demand response scheme with adaptive key evolution in smart grid" 25 (25): 2053-2064, 2014

17 R. Lu., "EPPA : An efficient and privacy-preserving aggregation scheme for secure smart grid communications" 23 (23): 1621-1632, 2012

18 M. Badra., "Design and performance analysis of a virtual ring architecture for smart grid privacy" 9 (9): 321-329, 2014

19 K. A. Shim, "An efficient ring signature scheme from pairings" 300 : 63-69, 2015

20 C. Meshram, "An efficient ID-based cryptographic encryption based on discrete logarithm problem and integer factorization problem" 115 : 351-358, 2015

21 Zhangjie Fu., "Achieving Efficient Cloud Search Services : Multi-keyword Ranked Search over Encrypted Cloud Data Supporting Parallel Computing" E98-B (E98-B): 190-200, 2015

22 M. Raghavendra., "A privacy preserving secure and efficient authentication scheme for telecare medical information systems" 39 : 2015

23 Ping Guo., "A Variable Threshold-value Authentication Architecture for Wireless Mesh Networks" 15 (15): 929-936, 2014