High Speed Hardware Architecture to Compute GF(p) Montgomery Inversion with Scalability Features

Modular inversion is a fundamental process in several cryptographic systems. It can be computed in software or hardware, but hardware computation has been proven to be faster and more secure. This research focused on improving an old scalable inversion hardware architecture proposed in 2004 for finite field GF(p). The architecture comprises two parts, a computing unit and a memory unit. The memory unit holds all the data bits of computation whereas the computing unit performs all the arithmetic operations in word (digit) by word bases such that the design is scalable. The main objective of this paper is to show the cost and benefit of modifying the memory unit to include shifting, which was previously one of the tasks of the scalable computing unit. The study included remodeling the entire hardware architecture removing the shifter from the scalable computing part and embedding it in the non-scalable memory unit instead. This modification resulted in a speedup to the complete inversion process with an area increase due to the new memory shifting unit. Several design schemes have been compared giving the user the complete picture to choose from depending on the application need

A Modulo Multiplication Hardware Design

Several modular multiplication algorithms have been reviewed. One modified modulo multiplication algorithm is chosen to be designed in simple hardware components. The proposed design is shown in blocks of the basic modules and the connections required between the basic components are shown in some details

High Speed Low Power GF(2k) Elliptic Curve Cryptography Processor Architecture

A new elliptic curve cryptographic processor architecture is proposed in this paper. It gives a choice of performance base depending on the importance of speed and/or power consumption. This flexibility is accomplished by utilizing the normal parallelism in the elliptic curve point operations. Scalable multipliers are adopted to compensate for the extra hardware due to parallelism instead of using the conventional parallel multipliers. It is shown in the paper that this parallelism can be exploited either to increase the speed of operation or to reduce power consumption by reducing the frequency of operation

Merging GF(p) Elliptic Curve Point Adding and Doubling on Pipelined VLSI Cryptographic ASIC Architecture

This paper merges between elliptic curve addition presents a modified processor architecture for Elliptic Curve Cryptography computations in Galois Fields GF(p). The architecture incorporates the methodology of pipelining to utilize the benefit of both parallel and serial implementations. It allows the exploitation of the inherited independency that exists in elliptic curve point addition and doubling operations using a single pipelined core. The processor architecture showed attraction because of its improvement over many parallel and serial implementations of elliptic curve crypto-systems. It proved to be efficient having better performance with regard to area, speed, and power consumption

New Hardware Algorithms and Designs for Montgomery Modular Inverse Computation in Galois Fields GF(p) and GF(2n)

The computation of the inverse of a number in finite fields, namely Galois Fields GF(p) or GF(2n), is one of the most complex arithmetic operations in cryptographic applications. In this work, we investigate the GF(p) inversion and present several phases in the design of efficient hardware implementations to compute the Montgomery modular inverse. We suggest a new correction phase for a previously proposed almost Montgomery inverse algorithm to calculate the inversion in hardware. It is also presented how to obtain a fast hardware algorithm to compute the inverse by multi-bit shifting method. The proposed designs have the hardware scalability feature, which means that the design can fit on constrained areas and still handle operands of any size. In order to have long-precision calculations, the module works on small precision words. The word-size, on which the module operates, can be selected based on the area and performance requirements. The upper limit on the operand precision is dictated only by the available memory to store the operands and internal results. The scalable module is in principle capable of performing infinite-precision Montgomery inverse computation of an integer, modulo a prime number. We also propose a scalable and unified architecture for a Montgomery inverse hardware that operates in both GF(p) and GF(2n) fields. We adjust and modify a GF(2n) Montgomery inverse algorithm to benefit from multi-bit shifting hardware features making it very similar to the proposed best design of GF(p) inversion hardware. We compare all scalable designs with fully parallel ones based on the same basic inversion algorithm. All scalable designs consumed less area and in general showed better performance than the fully parallel ones, which makes the scalable design a very efficient solution for computing the long precision Montgomery inverse

GF(2k) Elliptic Curve Cryptographic Processor Architecture Based on Bit Level Pipelined Digit Serial Multiplication

New processor architecture for elliptic curve encryption is proposed in this paper. The architecture exploits projective coordinates to convert GF(2k) division needed in elliptic point operations into several multiplication steps. The processor has three GF(2k) multipliers implemented using bit-level pipelined digit serial computation. It is shown that this results in a faster operation than using fully parallel multipliers with the added advantage of requiring less area. The proposed architecture is a serious contender for implementing data security systems based on elliptic curve cryptography

Hardware Model of an Expandable RSA Cryptographic System

Data security is an important aspect of information transmission and storage in an electronic form. Cryptographic systems are used to encrypt such information to guarantee its security. To retrieve such information, the encrypted form must be first decrypted. One of the most popular cryptographic systems is the RSA system. The security of the RSA-encrypted information largely depends on the size of the used encryption key. The larger the key size is the longer the encryption/decryption time will be. To cope with the continuous demand for larger key sizes, faster hardware implementations of the RSA algorithm has become an active area of research. One disadvantage of hardware implementations is their fixed key sizes. If the key size is to be increased, the hardware design should be fully replaced. The work reported here proposes an RSA hardware implementation that can be expanded as the key size gets larger. This implementation is modeled using VHDL in a parametrizable manner. Two other parameterized RSA hardware designs have also been VHDL modeled for comparison. The three models are compared for a 1024-bit key size and the results are analyzed. The complexity of the designs are compared and conclusions regarding optimal delay and area parameters are made

New Hardware Algorithms and Designs for Montgomery Modular Inverse Computation in Galois Fields GF(p) and GF(2n)

The computation of the inverse of a number in finite fields, namely Galois Fields GF(p) or GF(2n), is one of the most complex arithmetic operations in cryptographic applications. In this work, we investigate the GF(p) inversion and present several phases in the design of efficient hardware implementations to compute the Montgomery modular inverse. We suggest a new correction phase for a previously proposed almost Montgomery inverse algorithm to calculate the inversion in hardware. It is also presented how to obtain a fast hardware algorithm to compute the inverse by multi-bit shifting method. The proposed designs have the hardware scalability feature, which means that the design can fit on constrained areas and still handle operands of any size. In order to have long-precision calculations, the module works on small precision words. The word-size, on which the module operates, can be selected based on the area and performance requirements. The upper limit on the operand precision is dictated only by the available memory to store the operands and internal results. The scalable module is in principle capable of performing infinite-precision Montgomery inverse computation of an integer, modulo a prime number. We also propose a scalable and unified architecture for a Montgomery inverse hardware that operates in both GF(p) and GF(2n) fields. We adjust and modify a GF(2n) Montgomery inverse algorithm to benefit from multi-bit shifting hardware features making it very similar to the proposed best design of GF(p) inversion hardware. We compare all scalable designs with fully parallel ones based on the same basic inversion algorithm. All scalable designs consumed less area and in general showed better performance than the fully parallel ones, which makes the scalable design a very efficient solution for computing the long precision Montgomery inverse

Fast 160-Bits GF (P) Elliptic Curve Crypto Hardware of High-Radix Scalable Multipliers

In this paper, a fast hardware architecture for elliptic curve cryptography computation in Galois Field GF(p) is proposed. The architecture is implemented for 160-bits, as its data size to handle. The design adopts projective coordinates to eliminate most of the required GF(p) inversion calculations replacing them with several multiplication operations. The hardware is intended to be scalable, which allows the hardware to compute long precision numbers in a repetitive way. The design involves four parallel scalable multipliers to gain the best speed. This scalable design was implemented in different versions depending on the area and speed. All scalable implementations were compared with an available FPGA design. The proposed scalable hardware showed interesting results in both area and speed. It also showed some area-time flexibility to accommodate the variation needed by different crypto applications