云环境下集合隐私计算
作者:
基金项目:

国家自然科学基金(61272435,61373020)


Secure Set Computing in Cloud Environment
Author:
Fund Project:

National Natural Science Foundation of China (61272435, 61373020)

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    摘要:

    多方保密计算是网络空间安全与隐私保护的关键技术,基于同态加密算法的多方保密计算协议是解决云计算安全的一个重要工具.集合隐私计算是多方保密计算的基本问题,具有广泛的应用.现有的集合隐私计算方案多是基于两方的情况,基于多方的方案较少,效率较低,且这些方案都不能扩展到云计算平台.首先设计了一种编码方案,根据该编码方案和同态加密算法,在云计算环境下构造了一个具有普遍适用性且抗合谋的保密计算集合并集问题解决方案.该方案中的同态加密算法既可以是加法同态,又可以是乘法同态的加密算法.进一步利用哥德尔编码和ElGamal公钥加密算法构造了一种适用于云计算的高效集合并集计算方案.这些方案还可以对多个集合中的所有数据进行保密排序,并证明这些方案在半诚实模型下是安全的.所提方案经过简单改造,也可以保密地计算多个集合的交集.

    Abstract:

    Secure multiparty computation (SMC) is a key technology of cyberspace security and privacy preservation, and it is vital to provide secure cloud computing with SMC based on homomorphic encryption schemes. Secure set computing, which has extensive applications, is a fundamental problem in SMC. Existing solutions to secure set computing are mainly constructed between two parties, but less presented on multi-parties. Those schemes are inefficient, and are hardly adequate to cloud computing. This study proposes a new coding scheme and incorporates homomorphic encryption algorithm to construct a protocol for secure set union computing in cloud environment. The proposed scheme is universal and secure against the collusion of participants. The homomorphic encryption adopted can be either additive or multiplicative. The paper also proposes an efficient secure set union computing scheme, incorporating the G?del numbering and ElGamal public key encryption. The proposed schemes can be used to sort multiple sets, and are proved to be secure in the semi-honest model. In addition, with few modifications, the protocol can also securely compute the intersection of multiple sets.

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李顺东,周素芳,郭奕旻,窦家维,王道顺.云环境下集合隐私计算.软件学报,2016,27(6):1549-1565

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  • 收稿日期:2015-08-14
  • 最后修改日期:2015-10-09
  • 在线发布日期: 2016-01-22
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