SIPPA-2.0 - Secure information processing with privacy assurance (version 2.0)

Arun Prakash, K. krishnan, B. Sy
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引用次数: 4

Abstract

We present a two-party secure information processing protocol referred to as SIPPA-2.0 - targeted towards privacy preserving biometric data comparison and reconstruction. The original intention of SIPPA as reported previously is to enable private data comparison and reconstruction between a client and a server when (a) the client possesses some data that are “sufficiently similar” to that of the server, and (b) the server provides a scalar helper data to facilitate private data reconstruction by the client. In SIPPA-2.0, private data comparison and reconstruction are based on new theoretical results and a novel secure computation protocol referred to as SLSSP. These new results allow us to design and develop the much improved SIPPA and SLSSP protocols guaranteeing (a) security under semi-malicious model rather than just semi-honest model, and (b) privacy assurance with arbitrary reconstruction accuracy controllable by the server. Security analysis proving SLSSP secure under the semi-honest and semi-malicious models is presented. SIPPA-2.0 is applied to enable privacy preserving fingerprint comparison; where two parties can compare their fingerprint samples and can obtain a similarity score without revealing their raw fingerprint to each other. Experimental results on the accuracy of fingerprint matching and the run-time performance are also reported.
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SIPPA-2.0 -具有隐私保证的安全信息处理(2.0版)
我们提出了一种两方安全信息处理协议,称为SIPPA-2.0,旨在保护隐私的生物特征数据比较和重建。如前所述,SIPPA的初衷是在以下情况下实现客户机和服务器之间的私有数据比较和重建:(a)客户机拥有与服务器“足够相似”的一些数据,以及(b)服务器提供标量辅助数据以促进客户机的私有数据重建。在SIPPA-2.0中,私有数据的比较和重构是基于新的理论结果和一种新的安全计算协议(SLSSP)。这些新结果使我们能够设计和开发改进的SIPPA和SLSSP协议,以保证(a)在半恶意模型下而不仅仅是半诚实模型下的安全性,以及(b)由服务器控制的任意重构精度的隐私保证。通过安全分析证明了SLSSP在半诚实和半恶意模型下的安全性。采用SIPPA-2.0实现保密指纹比对;在不向对方透露原始指纹的情况下,双方可以比较各自的指纹样本并获得相似度分数。最后给出了指纹匹配精度和运行时性能的实验结果。
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