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

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

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

Efficient Scalable VLSI Architecture for Montgomery Inversion in GF(p)

The multiplicative inversion operation is a fundamental computation in several cryptographic applications. In this work, we propose a scalable VLSI hardware to compute the Montgomery modular inverse in GF(p). We suggest a new correction phase for a previously proposed almost Montgomery inverse algorithm to calculate the inversion in hardware. We also propose an efficient hardware algorithm to compute the inverse by multi-bit shifting method. The intended VLSI hardware is scalable, which means that a fixed-area module can handle operands of any size. The word-size, 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. This scalable hardware is compared with a previously proposed fixed (fully parallel) design showing very attractive results

Efficient Arithmetic for the Implementation of Elliptic Curve Cryptography

The technology of elliptic curve cryptography is now an important branch in public-key based crypto-system. Cryptographic mechanisms based on elliptic curves depend on the arithmetic of points on the curve. The most important arithmetic is multiplying a point on the curve by an integer. This operation is known as elliptic curve scalar (or point) multiplication operation. A cryptographic device is supposed to perform this operation efficiently and securely. The elliptic curve scalar multiplication operation is performed by combining the elliptic curve point routines that are defined in terms of the underlying finite field arithmetic operations. This thesis focuses on hardware architecture designs of elliptic curve operations. In the first part, we aim at finding new architectures to implement the finite field arithmetic multiplication operation more efficiently. In this regard, we propose novel schemes for the serial-out bit-level (SOBL) arithmetic multiplication operation in the polynomial basis over F_2^m. We show that the smallest SOBL scheme presented here can provide about 26-30\% reduction in area-complexity cost and about 22-24\% reduction in power consumptions for F_2^{163} compared to the current state-of-the-art bit-level multiplier schemes. Then, we employ the proposed SOBL schemes to present new hybrid-double multiplication architectures that perform two multiplications with latency comparable to the latency of a single multiplication. Then, in the second part of this thesis, we investigate the different algorithms for the implementation of elliptic curve scalar multiplication operation. We focus our interest in three aspects, namely, the finite field arithmetic cost, the critical path delay, and the protection strength from side-channel attacks (SCAs) based on simple power analysis. In this regard, we propose a novel scheme for the scalar multiplication operation that is based on processing three bits of the scalar in the exact same sequence of five point arithmetic operations. We analyse the security of our scheme and show that its security holds against both SCAs and safe-error fault attacks. In addition, we show how the properties of the proposed elliptic curve scalar multiplication scheme yields an efficient hardware design for the implementation of a single scalar multiplication on a prime extended twisted Edwards curve incorporating 8 parallel multiplication operations. Our comparison results show that the proposed hardware architecture for the twisted Edwards curve model implemented using the proposed scalar multiplication scheme is the fastest secure SCA protected scalar multiplication scheme over prime field reported in the literature

Efficient Implementation of Elliptic Curve Cryptography on FPGAs

This work presents the design strategies of an FPGA-based elliptic curve co-processor. Elliptic curve cryptography is an important topic in cryptography due to its relatively short key length and higher efficiency as compared to other well-known public key crypto-systems like RSA. The most important contributions of this work are: - Analyzing how different representations of finite fields and points on elliptic curves effect the performance of an elliptic curve co-processor and implementing a high performance co-processor. - Proposing a novel dynamic programming approach to find the optimum combination of different recursive polynomial multiplication methods. Here optimum means the method which has the smallest number of bit operations. - Designing a new normal-basis multiplier which is based on polynomial multipliers. The most important part of this multiplier is a circuit of size $O(n \log n)$ for changing the representation between polynomial and normal basis

Customisable arithmetic hardware designs

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Secure architectures for pairing based public key cryptography

Along with the growing demand for cryptosystems in systems ranging from large servers to mobile devices, suitable cryptogrophic protocols for use under certain constraints are becoming more and more important. Constraints such as calculation time, area, efficiency and security, must be considered by the designer. Elliptic curves, since their introduction to public key cryptography in 1985 have challenged established public key and signature generation schemes such as RSA, offering more security per bit. Amongst Elliptic curve based systems, pairing based cryptographies are thoroughly researched and can be used in many public key protocols such as identity based schemes. For hardware implementions of pairing based protocols, all components which calculate operations over Elliptic curves can be considered. Designers of the pairing algorithms must choose calculation blocks and arrange the basic operations carefully so that the implementation can meet the constraints of time and hardware resource area. This thesis deals with different hardware architectures to accelerate the pairing based cryptosystems in the field of characteristic two. Using different top-level architectures the hardware efficiency of operations that run at different times is first considered in this thesis. Security is another important aspect of pairing based cryptography to be considered in practically Side Channel Analysis (SCA) attacks. The naively implemented hardware accelerators for pairing based cryptographies can be vulnerable when taking the physical analysis attacks into consideration. This thesis considered the weaknesses in pairing based public key cryptography and addresses the particular calculations in the systems that are insecure. In this case, countermeasures should be applied to protect the weak link of the implementation to improve and perfect the pairing based algorithms. Some important rules that the designers must obey to improve the security of the cryptosystems are proposed. According to these rules, three countermeasures that protect the pairing based cryptosystems against SCA attacks are applied. The implementations of the countermeasures are presented and their performances are investigated

Studies on high-speed hardware implementation of cryptographic algorithms

Cryptographic algorithms are ubiquitous in modern communication systems where they have a central role in ensuring information security. This thesis studies efficient implementation of certain widely-used cryptographic algorithms. Cryptographic algorithms are computationally demanding and software-based implementations are often too slow or power consuming which yields a need for hardware implementation. Field Programmable Gate Arrays (FPGAs) are programmable logic devices which have proven to be highly feasible implementation platforms for cryptographic algorithms because they provide both speed and programmability. Hence, the use of FPGAs for cryptography has been intensively studied in the research community and FPGAs are also the primary implementation platforms in this thesis. This thesis presents techniques allowing faster implementations than existing ones. Such techniques are necessary in order to use high-security cryptographic algorithms in applications requiring high data rates, for example, in heavily loaded network servers. The focus is on Advanced Encryption Standard (AES), the most commonly used secret-key cryptographic algorithm, and Elliptic Curve Cryptography (ECC), public-key cryptographic algorithms which have gained popularity in the recent years and are replacing traditional public-key cryptosystems, such as RSA. Because these algorithms are well-defined and widely-used, the results of this thesis can be directly applied in practice. The contributions of this thesis include improvements to both algorithms and techniques for implementing them. Algorithms are modified in order to make them more suitable for hardware implementation, especially, focusing on increasing parallelism. Several FPGA implementations exploiting these modifications are presented in the thesis including some of the fastest implementations available in the literature. The most important contributions of this thesis relate to ECC and, specifically, to a family of elliptic curves providing faster computations called Koblitz curves. The results of this thesis can, in their part, enable increasing use of cryptographic algorithms in various practical applications where high computation speed is an issue

Fast bit-level, word-level and parallel arithmetic in finite fields for elliptic curve cryptosystems

Computer and network security has recently become a popular subject due to the explosive growth of the Internet and the migration of commerce practices to the electronic medium. Thus the authenticity and privacy of the information transmitted and the data stored on networked computers is of utmost importance. The deployment of network security procedures requires the implementation of cryptographic functions. More specifically, these include encryption, decryption, authentication, digital signature algorithms and message-digest functions. Performance has always been the most critical characteristic of a cryptographic function, which determines its effectiveness. In this thesis, we concentrate on developing high-speed algorithms and architectures for number theoretic cryptosystems. Our work is mainly focused on implementing elliptic curve cryptosystems efficiently, which requires space- and time-efficient implementations of arithmetic operations over finite fields. We introduce new methods for arithmetic operations over finite fields. Methodologies such as precomputation, residue number system representation, and parallel computation are adopted to obtain efficient algorithms that are applicable on a variety of cryptographic systems and subsystems. Since arithmetic operations in finite fields also have applications in coding theory and computer algebra, the methods proposed in this thesis are applicable to these applications as well