1 citations · 1 across the 5 of their papers we have counts for
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Sample-Preserving Search-to-Decision Reduction for Noisy Linear Equations over Large Moduli
Andrej Bogdanov, Kel Zin Tan, Prashant Nalini Vasudevan
The Noisy Linear Equations problem involves finding the solution to a random linear system over a finite field given noisy evaluations. This is a generalisation of various learning…
Towards Worst-case Hardness for Low-Noise LPN
Divesh Aggarwal, Rishav Gupta, Hai Hoang Nguyen +2
The hardness of the Learning Parity with Noise (LPN) problem is a foundational assumption in cryptography, forming the basis of constructions ranging from symmetric-key primitives…
Weak Zero-Knowledge and One-Way Functions
Rohit Chatterjee, Yunqi Li, Prashant Nalini Vasudevan
We study the implications of the existence of weak Zero-Knowledge (ZK) protocols for worst-case hard languages. These are protocols that have completeness, soundness, and zero-know…