Improved lower bound for the complexity of unique shortest vector problem

被引:0
|
作者
Jin, Baolong [1 ,2 ]
Xue, Rui [1 ,2 ]
机构
[1] Chinese Acad Sci, State Key Lab Informat Secur, Inst Informat Engn, Beijing 100085, Peoples R China
[2] Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 100049, Peoples R China
关键词
Computational complexity; Unique shortest vector problem; Bounded distance decoding; Complexity reduction; LATTICE; HARDNESS;
D O I
10.1186/s42400-023-00173-w
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unique shortest vector problem (uSVP) plays an important role in lattice based cryptography. Many cryptographic schemes based their security on it. For the cofidence of those applications, it is essential to clarify the complexity of uSVP with different parameters. However, proving the NP-hardness of uSVP appears quite hard. To the state of the art, we are even not able to prove the NP-hardness of uSVP with constant parameters. In this work, we gave a lower bound for the hardness of uSVP with constant parameters, i.e. we proved that uSVP is at least as hard as gap shortest vector problem (GapSVP) with gap of O(root n/ log(n)), which is in NP boolean AND coAM. Unlike previous works, our reduction works for paramters in a bigger range, especially when the constant hidden by the big-O in GapSVP is smaller than 1.
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页数:9
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