4 results sorted by ID
Universal Gaussian Elimination Hardware for Cryptographic Purposes
Jingwei Hu, Wen Wang, Kris Gaj, Donglong Chen, Huaxiong Wang
Implementation
In this paper, we investigate the possibility of performing Gaussian elimination for arbitrary binary matrices on hardware. In particular, we presented a generic approach for hardware-based Gaussian elimination, which is able to process both non-singular and singular matrices. Previous works on hardware-based Gaussian elimination can only process non-singular ones. However, a plethora of cryptosystems, for instance, quantum-safe key encapsulation mechanisms based on rank-metric codes, ROLLO...
A remark on the NIST 800-22 Binary Matrix Rank Test
Nicu Neculache, Vlad-Andrei Petcu, Emil Simion
Implementation
Statistical testing is a mechanism that has been included in various domains or fields, providing a method for making quantitative decisions about a particular sample. The statistical testing plays a big role in selecting and testing random and pseudorandom generators whose output may be used in the field of cryptography, specifically for the encryption, decryption and the keys or sub-keys generation. In this paper we study one of the NIST 800-22 random number generation tests. We give an...
Worst-Case Hardness for LPN and Cryptographic Hashing via Code Smoothing
Zvika Brakerski, Vadim Lyubashevsky, Vinod Vaikuntanathan, Daniel Wichs
Foundations
We present a worst case decoding problem whose hardness reduces to that of solving the Learning Parity with Noise (LPN) problem, in some parameter regime. Prior to this work, no worst case hardness result was known for LPN (as opposed to syntactically similar problems such as Learning with Errors). The caveat is that this worst case problem is only mildly hard and in particular admits a quasi-polynomial time algorithm, whereas the LPN variant used in the reduction requires extremely high...
McEliece in the world of Escher
Danilo Gligoroski, Simona Samardjiska, Håkon Jacobsen, Sergey Bezzateev
We present a new family of linear binary codes of length n and dimension k accompanied with a fast list decoding algorithm that can correct up to n/2 errors in a bounded channel with an error density $\rho$. The decisional problem of decoding random codes using these generalized error sets is NP-complete. Next we use the properties of these codes to design both an encryption scheme and a signature scheme. Although in the open literature there have been several proposals how to produce...
In this paper, we investigate the possibility of performing Gaussian elimination for arbitrary binary matrices on hardware. In particular, we presented a generic approach for hardware-based Gaussian elimination, which is able to process both non-singular and singular matrices. Previous works on hardware-based Gaussian elimination can only process non-singular ones. However, a plethora of cryptosystems, for instance, quantum-safe key encapsulation mechanisms based on rank-metric codes, ROLLO...
Statistical testing is a mechanism that has been included in various domains or fields, providing a method for making quantitative decisions about a particular sample. The statistical testing plays a big role in selecting and testing random and pseudorandom generators whose output may be used in the field of cryptography, specifically for the encryption, decryption and the keys or sub-keys generation. In this paper we study one of the NIST 800-22 random number generation tests. We give an...
We present a worst case decoding problem whose hardness reduces to that of solving the Learning Parity with Noise (LPN) problem, in some parameter regime. Prior to this work, no worst case hardness result was known for LPN (as opposed to syntactically similar problems such as Learning with Errors). The caveat is that this worst case problem is only mildly hard and in particular admits a quasi-polynomial time algorithm, whereas the LPN variant used in the reduction requires extremely high...
We present a new family of linear binary codes of length n and dimension k accompanied with a fast list decoding algorithm that can correct up to n/2 errors in a bounded channel with an error density $\rho$. The decisional problem of decoding random codes using these generalized error sets is NP-complete. Next we use the properties of these codes to design both an encryption scheme and a signature scheme. Although in the open literature there have been several proposals how to produce...
