Reusable Fuzzy Extractor from LWE

摘要：

　　Fuzzy extractor converts the reading of a noisy non-uniform source to a reproducible and almost uniform output R.The output R in turn is used in some cryptographic system as a secret key.To enable multiple extractions of keys R1, R2,..., Rρ from the same noisy non-uniform source and applications of different Ri, the concept of reusable fuzzy extractor is proposed to guarantee the pseudorandomness of Ri even conditioned on other extracted keys Rj (from the same source).In this work, we construct a reusable fuzzy extractor from the Learning With Errors (LWE) assumption.Our reusable fuzzy extractor provides resilience to linear fraction of errors.Moreover, our construction is simple and efficient and imposes no special requirement on the statistical structure of the multiple readings of the source.

作者: Yunhua Wen Shengli Liu

作者单位: Dept.of Computer Science and Engineering,Shanghai Jiao Tong University, Shanghai 200240, China;State Dept.of Computer Science and Engineering,Shanghai Jiao Tong University, Shanghai 200240, China;State

会议类型: 国际会议

会议名称: 中国密码学会2018年密码算法学术会议

会议地点: 广州

会议语种:英文

页码: 117-130

在线出版日期: 2018-05-01（万方平台首次上网日期，不代表论文的发表时间）