The Low Resource Hardware Implementation And Optimization Of UOV Signature Scheme And Hyper-O Signature Scheme

Public key cryptography has always been one of the key technologies in secure communications. The two most common ways of using asymmetric cryptography is key association which is used for establishing secure communication channel, and digital signature which is used for confirmation of the source of information.As the mobile technology develops, mobile devices such as smart cards and RFIDs are already well known by the public. Using mobile device for payment or financial activities has become reality. However, such mobile device has low storage space and low capability for calculation, makes it very difficult to use traditional asymmetric algorithms such as RSA for security purpose. By comparison, MPKC has fewer demands on calculation, and has much potential on such area. Furthermore, as the development of quantum computer, in polynomial time solving the arithmetic problems that RSA and ECC rely on is possible, RSA and ECC may have potential security problems. But nothing solid has been found that any algorithms can solve the MQ problem in polynomial time, which MPKC relies on.Though it’s been more than twenty years since the birth of MPKC, the security of MPKC hasn’t been proved fully. The encryption-decryption schemes are not so well functioned. But the signature schemes are proved to be secure and efficient. UOV scheme is a mature secure signature scheme which was proposed more than ten years ago. And Hyper-O is a new proposed scheme. The common feature of these two is they are all trying to using linear equations for trapdoors. Traditional design and attacks are mostly focused on finite field characterize as2. Such finite fields may take advantages of computer’s binary system when doing calculations. But based on recent study and experiments, finite fields characterized using odd numbers such as3,5and31are harder to crack.This paper tends to use GF (31) to implements UOV and Hyper-O schemes on hardware. This paper first optimizes the arithmetic calculators, then using finite states machine, matrix multiplier and micro instructors to implement these schemes. And after doing several optimizations using the estimation of the internal results, it finally gets two low area low power consuming implementations of MPKC schemes.