Low Complexity Bit-Parallel Square Root Computation over GF(2m2^m) for all Trinomials

In this contribution we introduce a low-complexity bit-parallel algorithm for computing square roots over binary extension fields. Our proposed method can be applied for any type of irreducible polynomials. We derive explicit formulae for the space and time complexities associated to the square root operator when working with binary extension fields generated using irreducible trinomials. We show that for those finite fields, it is possible to compute the square root of an arbitrary field element with equal or better hardware efficiency than the one associated to the field squaring operation. Furthermore, a practical application of the square root operator in the domain of field exponentiation computation is presented. It is shown that by using as building blocks squarers, multipliers and square root blocks, a parallel version of the classical square-and-multiply exponentiation algorithm can be obtained. A hardware implementation of that parallel version may provide a speedup of up to 50\% percent when compared with the traditional version

Fast Montgomery-like Square Root Computation over GF(2m)GF(2^m) for All Trinomials

This letter is concerned with an extension of square root computation over $GF(2^m)$ defined by irreducible trinomials. We introduce a new type of Montgomery-like square root formulae, which is more efficient compared with classic square root operation. By choosing proper Montgomery factor regarding to different types of trinomials, the space and time complexities of our proposal outperform or match the best results. Furthermore, a practical application of the Montgomery-like square root in exponentiation computation is also presented

New bit-parallel Montgomery multiplier for trinomials using squaring operation

In this paper, a new bit-parallel Montgomery multiplier for $GF(2^m)$ is presented, where the field is generated with an irreducible trinomial. We first present a slightly generalized version of a newly proposed divide and conquer approach. Then, by combining this approach and a carefully chosen Montgomery factor, the Montgomery multiplication can be transformed into a composition of small polynomial multiplications and Montgomery squarings, which are simpler and more efficient. Explicit complexity formulae in terms of gate counts and time delay of our architecture are investigated. As a result, the proposed multiplier has generally 25\% lower space complexity than the fastest multipliers, with time complexity as good as or better than previous Karatsuba-based multipliers for the same class of fields. Among the five irreducible polynomials recommended by NIST for the ECDSA (Elliptic Curve Digital Signature Algorithm), there are two trinomials which are available for our architecture. We show that our proposal outperforms the previous best known results if the space and time complexity are both considered

Efficient Bit-parallel Multiplication with Subquadratic Space Complexity in Binary Extension Field

Bit-parallel multiplication in GF(2^n) with subquadratic space complexity has been explored in recent years due to its lower area cost compared with traditional parallel multiplications. Based on \u27divide and conquer\u27 technique, several algorithms have been proposed to build subquadratic space complexity multipliers. Among them, Karatsuba algorithm and its generalizations are most often used to construct multiplication architectures with significantly improved efficiency. However, recursively using one type of Karatsuba formula may not result in an optimal structure for many finite fields. It has been shown that improvements on multiplier complexity can be achieved by using a combination of several methods. After completion of a detailed study of existing subquadratic multipliers, this thesis has proposed a new algorithm to find the best combination of selected methods through comprehensive search for constructing polynomial multiplication over GF(2^n). Using this algorithm, ameliorated architectures with shortened critical path or reduced gates cost will be obtained for the given value of n, where n is in the range of [126, 600] reflecting the key size for current cryptographic applications. With different input constraints the proposed algorithm can also yield subquadratic space multiplier architectures optimized for trade-offs between space and time. Optimized multiplication architectures over NIST recommended fields generated from the proposed algorithm are presented and analyzed in detail. Compared with existing works with subquadratic space complexity, the proposed architectures are highly modular and have improved efficiency on space or time complexity. Finally generalization of the proposed algorithm to be suitable for much larger size of fields discussed

Reconfigurable elliptic curve cryptography

Elliptic Curve Cryptosystems (ECC) have been proposed as an alternative to other established public key cryptosystems such as RSA (Rivest Shamir Adleman). ECC provide more security per bit than other known public key schemes based on the discrete logarithm problem. Smaller key sizes result in faster computations, lower power consumption and memory and bandwidth savings, thus making ECC a fast, flexible and cost-effective solution for providing security in constrained environments. Implementing ECC on reconfigurable platform combines the speed, security and concurrency of hardware along with the flexibility of the software approach. This work proposes a generic architecture for elliptic curve cryptosystem on a Field Programmable Gate Array (FPGA) that performs an elliptic curve scalar multiplication in 1.16milliseconds for GF (2163), which is considerably faster than most other documented implementations. One of the benefits of the proposed processor architecture is that it is easily reprogrammable to use different algorithms and is adaptable to any field order. Also through reconfiguration the arithmetic unit can be optimized for different area/speed requirements. The mathematics involved uses binary extension field of the form GF (2n) as the underlying field and polynomial basis for the representation of the elements in the field. A significant gain in performance is obtained by using projective coordinates for the points on the curve during the computation process

Mastrovito Form of Non-recursive Karatsuba Multiplier for All Trinomials

We present a new type of bit-parallel non-recursive Karatsuba multiplier over $GF(2^m)$ generated by an arbitrary irreducible trinomial. This design effectively exploits Mastrovito approach and shifted polynomial basis (SPB) to reduce the time complexity and Karatsuba algorithm to reduce its space complexity. We show that this type of multiplier is only one $T_X$ slower than the fastest bit-parallel multiplier for all trinomials, where $T_X$ is the delay of one 2-input XOR gate. Meanwhile, its space complexity is roughly 3/4 of those multipliers. To the best of our knowledge, it is the first time that our scheme has reached such a time delay bound. This result outperforms previously proposed non-recursive Karatsuba multipliers

Low Complexity Cubing and Cube Root Computation over \F_{3^m} in Polynomial Basis

We present low complexity formulae for the computation of cubing and cube root over \F_{3^m} constructed using special classes of irreducible trinomials, tetranomials and pentanomials. We show that for all those special classes of polynomials, field cubing and field cube root operation have the same computational complexity when implemented in hardware or software platforms. As one of the main applications of these two field arithmetic operations lies in pairing-based cryptography, we also give in this paper a selection of irreducible polynomials that lead to low cost field cubing and field cube root computations for supersingular elliptic curves defined over \F_{3^m}, where $m$ is a prime number in the pairing-based cryptographic range of interest, namely, $m\in [47, 541]$

Synthesis Optimization on Galois-Field Based Arithmetic Operators for Rijndael Cipher

A  series  of  experiments  has  been  conducted  to  show  that  FPGA synthesis  of  Galois-Field  (GF)  based  arithmetic  operators  can  be  optimized automatically  to  improve  Rijndael  Cipher  throughput.  Moreover,  it  has  been demonstrated  that  efficiency  improvement  in  GF  operators  does  not  directly correspond to the system performance at application level. The experiments were motivated by so many research works that focused on improving performance of GF  operators.  Each  of  the  variants  has  the  most  efficient  form  in  either  time (fastest) or space  (smallest occupied area) when implemented in FPGA chips. In fact,  GF  operators are not utilized  individually, but  rather integrated one to the others to  implement algorithms.  Contribution  of  this  paper  is  to  raise  issue  on GF-based  application  performance  and  suggest  alternative  aspects  that potentially  affect  it.  Instead  of  focusing  on  GF  operator  efficiency,  system characteristics are worth considered in optimizing application performance