%0 Journal Article
%T High Throughput Pseudorandom Number Generator Based on Variable Argument Unified Hyperchaos
%A Kaiyu Wang
%A Qingxin Yan
%A Shihua Yu
%A Xianwei Qi
%A Yudi Zhou
%A Zhenan Tang
%J VLSI Design
%D 2014
%I Hindawi Publishing Corporation
%R 10.1155/2014/923618
%X This paper presents a new multioutput and high throughput pseudorandom number generator. The scheme is to make the homogenized Logistic chaotic sequence as unified hyperchaotic system parameter. So the unified hyperchaos can transfer in different chaotic systems and the output can be more complex with the changing of homogenized Logistic chaotic output. Through processing the unified hyperchaotic 4-way outputs, the output will be extended to 26 channels. In addition, the generated pseudorandom sequences have all passed NIST SP800-22 standard test and DIEHARD test. The system is designed in Verilog HDL and experimentally verified on a Xilinx Spartan 6 FPGA for a maximum throughput of 16.91£¿Gbits/s for the native chaotic output and 13.49£¿Gbits/s for the resulting pseudorandom number generators. 1. Introduction Pseudorandom number (PN) is the 01 sequence which has the randomness similar to noise. It has been widely used in digital communication, cryptography, computer games, and numerical computation [1¨C3]. Chaos is the phenomenon which shows very complex nonlinear dynamic characteristics in a deterministic system. And it has excellent properties such as nonperiodicity, broad bandwidth, and sensitivity to initial value [4, 5]. So Chaos and PN have a natural link. And compared to other PN sequences like m sequences, and so forth, the PN sequence generated by chaotic system has advantages like larger key space, longer cycle, and so forth. Currently, researches of chaotic pseudorandom number generator (PRNG) are more focused on the digital implementation of low dimensional chaos such as Logistic chaos, Tent chaos, and Lorenz chaos. While these algorithms have significant advantages in some respects, like simpler construction, fewer resources consuming, and faster computing speed, they also have the fatal weakness that cannot be ignored to PRNG like smaller secret key space, periodic problem, and relatively lower throughput. Therefore, implementing a PRNG based on higher-order chaos equations seems more advantage because the hyperchaos has multiple positive Lyapunov exponent and more controllable parameters and the output of system will have more complex randomness. The hyperchaotic encryption signal is harder to decode than low dimensional encryption signal [6]. And hyperchaos can provide multiple outputs, improve the throughput, and process multiple target signal [7, 8]. In 2002, Lu et al. proposed the unified chaos that can make Lorenz chaos, Lu chaos, and Chen chaos into a unified chaotic system and realize continued transition from one to another [9]. In
%U http://www.hindawi.com/journals/vlsi/2014/923618/