This study presents two new bit-parallel cellular multipliers based on an irreducible all one polynomial (AOP) over the finite field GF(2m). Using the property of the AOP, this work also presents an efficient algorithm of inner-product multiplication for computing AB2 multiplications is proposed, with a structure that can simplify the time and space complexity for hardware implementations. The first structure employs the new inner-product multiplication algorithm to construct the bit-parallel cellular architecture. The designed multiplier only requires the computational delays of (m+1)(TAND+TXOR). The second proposed structure is a modification of the first structure, and it requires (m+2) TXOR delays. Moreover, the proposed multipliers can perform A2iB2j computations by shuffling the coefficients to make i and j integers. For the computing multiplication in GF(2m), the novel multipliers turn out to be efficient as they simplify architecture and accelerate computation. The two novel architectures are highly regular, simpler, and have shorter computation delays than the conventional cellular multipliers.

In this paper, a generalized Montgomery multiplication algorithm in GF(2m) using the Toeplitz matrix-vector representation is presented. The hardware architectures derived from this algorithm provide low-complexity bit-parallel systolic multipliers with trinomials and pentanomials. The results reveal that our proposed multipliers reduce the space complexity of approximately 15% compared with an existing systolic Montgomery multiplier for trinomials. Moreover, the proposed architectures have the features of regularity, modularity, and local interconnection. Accordingly, they are well suited to VLSI implementation.

Normal and dual bases are two popular representation bases for elements in GF(2m). In general, each distinct representation basis has its associated different hardware architecture. In this paper, we will present a unified systolic array multiplication architecture for both normal and dual bases, such a unified multiplication architecture is termed a Hankel multiplier. The Hankel multiplier has lower space complexity while compared with other existing normal basis multipliers and dual basis multipliers.

This investigation proposes a new multiplication algorithm in the finite field GF(2m) over the polynomial basis, in which the irreducible xm +xn + 1 with gcd(m,n) = 1 generates the field GF(2m). The algorithm involves two steps--the intermediate multiplication and the modulo reduction. In the first step, the intermediate multiplication algorithm permutes a polynomial to construct the full-bit-parallel systolic intermediate multiplier. The circuit is identical of m2 cells, each cell is identical of one 2-input AND gate, one 2-input XOR gate, and four 1-bit latches. In the second step, based on the results of the intermediate multiplication in the first step, the modulo reduction circuit is built using regular and simple reduction operations. The latency of the proposed multiplier requires m + k + 1 clock cycles, where k = + 1. Notably, the latency can be very low if n is in the range 1 n . For the computing multiplication in GF(2m), the novel multiplier exhibits much lower latency than the existing systolic multipliers, and is well suited to VLSI systems due to their regular interconnection pattern, modular structure and fully inherent parallelism.

This work presents a novel scalable and systolic Montgomery's algorithm in GF(2m). The proposed algorithm is based on the Toeplitz matrix-vector representation, which obtains the scalable and systolic Montgomery multiplier in a flexible manner, and can adapt to the required precision. Analytical results indicate that the proposed multiplier over the generic field of GF(2m) has a latency of d+n(2n+1), where n = m / d , and d denotes the selected digital size. The latency is reduced to d+n(n+1) clock cycles when the field is constructed from generalized equally-spaced polynomials. Since the selected digital size is d ≥5 bits, the proposed architectures have lower time-space complexity than traditional digit-serial multipliers. Moreover, the proposed architectures have regularity, modularity and local interconnect ability, making them very suitable for VLSI implementation.

Because fault-based attacks on cryptosystems have been proven effective, fault diagnosis and tolerance in cryptography have started a new surge of research and development activity in the field of applied cryptography. Without magnitude comparisons, the Montgomery multiplication algorithm is very attractive and popular for Elliptic Curve Cryptosystems. This paper will design a Montgomery multiplier array with a bit-parallel architecture in GF(2m) with concurrent error detection capability to protect it against fault-based attacks. The robust Montgomery multiplier array with concurrent error detection requires only about 0.2% extra space overhead (if m=512 is as an example) and requires four extra clock cycles compared to the original Montgomery multiplier array without concurrent error detection.