FPGA based trustworthy authentication technique using Physically Unclonable Functions and artificial intelligence

Field Programmable Gate Arrays (FPGAs) need built-in security not only to prevent reverse engineering, but also to prevent hacking and cloning while reconfiguring or partially reconfiguring the devices. To counter such threats, methodologies for preventing IC piracy have been developed that require a unique signature key for every fabricated chip. Physically Unclonable Functions (PUFs) can be used for such signature generation. This paper presents a design for cryptographic applications that can be implemented on an FPGA taking advantage of its unique architecture. The research is divided into three parts: The first part of the research involves development of techniques for the generation of uniquely distinguishable responses from Ring Oscillator PUFs. The second part involves development of error correction technique using Artificial Neural Networks. The third part involves a hashing function to redress the response bits. The proposed design is implemented on several Xilinx Spartan FPGAs and the Hamming distances for the responses are computed and analyzed. The uniqueness of the responses is found to be 49.0625%. It is also found that the results of the proposed error correction code are computationally efficient as compared to the conventional BCH codes.