轻量级的数据融合隐私保护算法

doi:10.11772/j.issn.1001-9081.2014.08.2336

计算机应用 ›› 2014, Vol. 34 ›› Issue (8): 2336-2341.DOI: 10.11772/j.issn.1001-9081.2014.08.2336

轻量级的数据融合隐私保护算法

陈燕俐¹,²,傅春福¹,许建¹,²,杨庚³

1. 南京邮电大学计算机学院，南京210003
2. 南京邮电大学宽带无线通信与传感网技术教育部重点实验室，南京210003
3. 南京邮电大学计算机学院,南京 210003

收稿日期:2014-02-21 修回日期:2014-03-28 出版日期:2014-08-01 发布日期:2014-08-10
通讯作者: 傅春福
作者简介:陈燕俐（1969-），女，江苏镇江人，教授，博士研究生，主要研究方向：云计算、信息安全、隐私保护；傅春福（1989-），男，江苏南京人，硕士研究生，主要研究方向：信息安全、隐私保护；许建（1980-），男，江苏徐州人，副教授，博士研究生，主要研究方向：计算机网络、信息安全、隐私保护；杨庚（1961-），男，江苏建湖人，教授，博士生导师,主要研究方向:计算机通信与网络、网络安全、分布与并行计算。
基金资助:
国家973计划项目;国家自然科学基金资助项目;江苏省自然科学基金资助项目

Lightweight privacy-preserving data aggregation algorithm

CHEN Yanli¹,²,FU Chunjuan²,XU Jian¹,²,YANG Geng²

1. Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education, Nanjing Jiangsu 210003, China
2. School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing Jiangsu 210003, China;

Received:2014-02-21 Revised:2014-03-28 Online:2014-08-01 Published:2014-08-10
Contact: FU Chunjuan

摘要/Abstract

摘要：

针对隐私数据易受数据机密性、完整性和新鲜性攻击这一问题，提出了一种基于同态Hash函数的无线传感器网络(WSN)数据融合隐私保护算法——HPDA算法。利用同态加密算法保证了融合数据的机密性，通过构建同态Hash函数进行数据的完整性和新鲜性检测，通过改进的ID传输机制减少系统的通信开销。理论分析和实验仿真结果表明，HPDA算法在无线传感器网络数据融合过程中具有良好的数据机密性、完整性和新鲜性保护，且具有较低的通信开销。

Abstract:

Private data is easy to suffer from the attacks about data confidentiality, integrity and freshness. To resolve this problem, a secure data aggregation algorithm based on homomorphic Hash function was proposed, called HPDA (High-Efficiency Privacy Preserving Data Aggregation) algorithm. Firstly, it used homomorphic encryption scheme to provide data privacy-preserving. Secondly, it adopted homomorphic Hash function to verify the integrity and freshness of aggregated data. Finally, it reduced the communication overhead of the system by improved ID transmission mechanism. The theoretical analyses and experimental simulation results show that HPDA can effectively preserve data confidentiality, check data integrity, satisfy data freshness, and bring low communication overhead.

中图分类号:

陈燕俐傅春福许建杨庚. 轻量级的数据融合隐私保护算法[J]. 计算机应用, 2014, 34(8): 2336-2341.

CHEN Yanli FU Chunjuan XU Jian YANG Geng. Lightweight privacy-preserving data aggregation algorithm[J]. Journal of Computer Applications, 2014, 34(8): 2336-2341.

参考文献

［1］MUNI V K, KANDASAMY A, CHANDRASEKARAN K. Energy-efficient edge-based network partitioning scheme for wireless sensor networks ［C］// Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics. Piscataway: IEEE Press, 2013: 1017-1022.
［2］STEFFEN P, WESTHOFF D. A survey on the encryption of convergecast traffic with in-network processing ［J］. IEEE Transactions on Dependable and Secure Computing, 2010, 7(1): 20-34.
［3］MARRIWALA N, RATHEE P. An approach to increase the wireless sensor network lifetime ［C］// Proceedings of the 2012 World Congress on Information and Communication Technologies. Piscataway: IEEE Press, 2012: 495-499.
［4］CAYIRPUNAR O, TAVLI B. The impact of base station mobility patterns on wireless sensor network lifetime ［C］// Proceedings of the 24th IEEE International Symposium on Personal Indoor and Mobile Radio Communications. Piscataway: IEEE Press, 2013: 2701-2706.
［5］LI N, ZHANG N, BHAVANI T, et al. Privacy preservation in wireless sensor networks: a state-of-the-art survey ［J］. Ad Hoc Networks, 2009, 7(8): 1501-1514.
［6］HAIYING S, LIANYU Z. ALERT: an anonymous location-based efficient routing protocol in MANETs ［J］. IEEE Transactions on Mobile Computing, 2013, 6(4): 1079-1093.
［7］KIM Y, LEE H, YOON M, et al. Hilbert-curve based data aggregation scheme to enforce data privacy and data integrity for wireless sensor networks ［J］. International Journal of Distributed Sensor Networks, 2013, 2013: 1-14.
［8］HE W B, NGUYEN H, LIU X. iPDA: an integrity-protecting private data aggregation scheme for wireless sensor networks ［C］// Proceedings of the 2008 IEEE Military Communications Conference. Piscataway: IEEE Press, 2008: 1-7.
［9］YANG G, LI S, XU X L, et al. Precision-enhanced and encryption-mixed privacy-preserving data aggregation in wireless sensor networks ［J］. International Journal of Distributed Sensor Networks, 2013, 2013(4): 30-41.
［10］FAGEN L, PAN X. Practical secure communication for integrating wireless sensor networks into the Internet of things ［J］. Sensors Journal, 2013, 13(10): 3677-3684.
［11］HE W, LIU X, NGUYEN H. A cluster-based protocol to enforce integrity and preserve privacy in data aggregation ［C］// Proceedings of the 29th IEEE International Conference on Distributed Computing Systems Workshops. Piscataway: IEEE Press, 2009: 14-19.
［12］AGRAWAL R, SRIKNAT R. Privacy-preserving data mining ［C］// Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data. New York: ACM Press, 2009: 439-450.
［13］HUANG Z L, DU W L, CHEN B. Deriving private information from randomized data ［C］// Proceedings of the ACM SIGMOD International Conference on Management of Data. New York: ACM Press, 2005: 37-48.
［14］DOMINGO F J, HERRERA J. A new privacy homomorphism and applications ［J］. Information Processing Letters, 1996, 60(5): 277-282.
［15］CASTELLUCCIA C, MYKLENTN E, TSUDIK G. Efficient aggregation of encrypted data in wireless sensor networks ［C］// Proceedings of the Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services. Piscataway: IEEE Press, 2005: 109-117.
［16］HU L X, EVANS D. Secure aggregation for wireless networks ［C］// Proceedings of the 2003 Symposium on Applications and the Internet Workshops. Washington, DC: IEEE Computer Society, 2011: 384-391.
［17］RABINDRA B, HYE K Y. Achieving scalable privacy preserving data aggregation for wireless sensor networks ［C］// Proceedings of the 10th IEEE International Conference on Computer and Information Technology. Washington, DC: IEEE Computer Society, 2010: 1962-1969.

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轻量级的数据融合隐私保护算法

Lightweight privacy-preserving data aggregation algorithm

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