Design and FPGA implementation of Lorenz key generator for information security

Design and FPGA implementation of Lorenz key generator for information security

Nandha kumar S

PG Student, Department of ECE

PSG College of Technology Coimbatore, India s.nandhakumar333@gmail.com

Dr. J. Ramesh Professor,

Department of ECE, PSG college of Technology,

Coimbatore, India jramesh60@yahoo.com

P. Vivek Karthick

Assistant Professor, Department of ECE,

SONA college of Technology, Salem, India vivekmalar@gmail.com

Abstract— In recent years, enormous amount of information obtained from digital media, are available through the Internet, satellites, mobiles and other sources making it possible to access these contents. Thus, protecting information from unauthorized access has become a major task for researchers as the usual encryption systems are unable to resist the evolution of hacker attacks. The advantages of Lorenz key is encryption is faster, very secure transmission and storage when compared to the other key. Many cryptosystems based on the generation of Lorenz key for hiding messages, using chaotic systems as a generator for those sequences have been gaining attention recently. The chaos is generated from a nonlinear dynamic system, known for its aperiodicity, randomness and sensitivity with respect to initial values and control parameters. This work presents an approach for a real-time FPGA implementation of a random key, based on Lorenz's chaotic generator for information security. At first, the Lorenz chaotic oscillator model is designed using MATLAB code. The performance is successfully verified, and the model is constructed using MATLAB-Simulink model. Simulink models in MATLAB provide a modelling environment that is well suited for hardware design. Then, the model is converted to Xilinx System Generator model. The Xilinx system generator technology is used for the conception of the Lorenz chaotic system and for generating the code. This code is then dumped to configure the FPGA.

Keywords— Chaos, Lorenz, MATLAB, Simulink, Xilinx System Generator, FPGA