One random jump and one permutation: sufficient conditions to chaotic, statistically faultless, and large throughput PRNG for FPGA
This provides a faster, statistically robust pseudorandom number generator for FPGA applications in information security, though it appears incremental as a post-treatment method.
The authors introduced a new chaos-based pseudorandom number generator for FPGA that uses a Hamilton cycle deletion and permutation to improve statistical quality while maintaining speed, achieving 6.7 Gbps throughput and passing stringent TestU01 tests.
Sub-categories of mathematical topology, like the mathematical theory of chaos, offer interesting applications devoted to information security. In this research work, we have introduced a new chaos-based pseudorandom number generator implemented in FPGA, which is mainly based on the deletion of a Hamilton cycle within the $n$-cube (or on the vectorial negation), plus one single permutation. By doing so, we produce a kind of post-treatment on hardware pseudorandom generators, but the obtained generator has usually a better statistical profile than its input, while running at a similar speed. We tested 6 combinations of Boolean functions and strategies that all achieve to pass the most stringent TestU01 battery of tests. This generation can reach a throughput/latency ratio equal to 6.7 Gbps, being thus the second fastest FPGA generator that can pass TestU01.