RankSynd a PRNG Based on Rank Metric
This work addresses the need for efficient and secure PRNGs in cryptography, particularly for applications requiring resistance to quantum attacks, though it appears incremental as it builds on existing rank metric concepts.
The authors tackled the problem of designing a fast pseudo-random number generator (PRNG) with small public data by leveraging the syndrome decoding problem for rank metric codes, and they found that this approach avoids the need for additional structures like quasi-cyclicity used in Hamming distance methods.
In this paper, we consider a pseudo-random generator based on the difficulty of the syndrome decoding problem for rank metric codes. We also study the resistance of this problem against a quantum computer. Our results show that with rank metric it is possible to obtain fast PRNG with small public data, without considering additional structure for public matrices like quasi-cyclicity for Hamming distance.