Input Locality and Hardness Amplification

AbstractWe establish new hardness amplification results for one-way functions in which each input bit influences only a small number of output bits (a.k.a. input-local functions). Our transformations differ from previous ones in that they approximately preserve input locality and at the same time retain the input size of the original function.Let f:{0,1}n→{0,1}m be a one-way function with input locality d, and suppose that f cannot be inverted in time $\exp(\tilde{O}(\sqrt{n}\cdot d))$ on an ε-fraction of inputs. Our main results can be summarized as follows: If f is injective then it is equally hard to invert f on a (1−ε)-fraction of inputs.If f is regular then there is a function g:{0,1}n→{0,1}m+O(n) that is d+O(log3n) input local and is equally hard to invert on a (1−ε)-fraction of inputs. A natural candidate for a function with small input locality and for which no sub-exponential time attacks are known is Goldreich’s one-way function. To make our results applicable to this function, we prove that when its input locality is set to be d=O(logn) certain variants of the function are (almost) regular with high probability.In some cases, our techniques are applicable even when the input locality is not small. We demonstrate this by extending our first main result to one-way functions of the “parity with noise” type.

[1]  Yuval Ishai,et al.  Cryptography in NC0 , 2004, FOCS.

[2]  Oded Goldreich,et al.  Candidate One-Way Functions Based on Expander Graphs , 2011, Studies in Complexity and Cryptography.

[3]  Russell Impagliazzo,et al.  One-way functions are essential for complexity based cryptography , 1989, 30th Annual Symposium on Foundations of Computer Science.

[4]  Noam Nisan,et al.  The computational complexity of universal hashing , 1990, Proceedings Fifth Annual Structure in Complexity Theory Conference.

[5]  Luca Trevisan,et al.  On Hardness Amplification of One-Way Functions , 2005, TCC.

[6]  Alessandro Panconesi,et al.  Concentration of Measure for the Analysis of Randomized Algorithms , 2009 .

[7]  Andrew Chi-Chih Yao,et al.  Theory and application of trapdoor functions , 1982, 23rd Annual Symposium on Foundations of Computer Science (sfcs 1982).

[8]  Leonid A. Levin,et al.  Pseudo-random generation from one-way functions , 1989, STOC '89.

[9]  Luca Trevisan,et al.  Goldreich's One-Way Function Candidate and Myopic Backtracking Algorithms , 2009, TCC.

[10]  Richard M. Karp,et al.  The rank of sparse random matrices over finite fields , 1997 .

[11]  Hugo Krawczyk,et al.  On the Existence of Pseudorandom Generators , 1988, CRYPTO.

[12]  Andrew Chi-Chih Yao,et al.  Theory and Applications of Trapdoor Functions (Extended Abstract) , 1982, FOCS.

[13]  Omer Reingold,et al.  On the Power of the Randomized Iterate , 2006, SIAM J. Comput..

[14]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[15]  Leonid A. Levin,et al.  Security preserving amplification of hardness , 1990, Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science.

[16]  Avi Wigderson,et al.  Public-key cryptography from different assumptions , 2010, STOC '10.

[17]  篠原 祝子,et al.  幼稚園教育実習における実習態度 : 平成22年度6月「幼稚園実習」の実習園評価と実習生評価の比較 , 2011 .

[18]  Adam Tauman Kalai,et al.  Noise-tolerant learning, the parity problem, and the statistical query model , 2000, STOC '00.

[19]  Youming Qiao,et al.  On the security of Goldreich’s one-way function , 2011, computational complexity.

[20]  Yuval Ishai,et al.  Cryptography with Constant Input Locality , 2007, Journal of Cryptology.

[21]  Noga Alon,et al.  The Probabilistic Method , 2015, Fundamentals of Ramsey Theory.