Bit-Parallel GF(2n)GF(2^{n}) Squarer Using Shifted Polynomial Basis

We present explicit formulae and complexities of bit-parallel shifted polynomial basis (SPB) squarers in finite field $GF(2^{n})$s generated by general irreducible trinomials $x^{n}+x^{k}+1$ ($0< k <n$) and type-II irreducible pentanomials $x^{n}+x^{k+1}+x^{k}+x^{k-1}+1$ ($3<k<(n-3)/2$). The complexities of the proposed squarers match or slightly outperform the previous best results. These formulae can also be used to design polynomial basis Montgomery squarers without any change. Furthermore, we show by examples that XOR gate numbers of SPB squarers are different when different shift factors in the SPB definition, i.e., parameter $v$ in ${\{}x^{i-v}|0\leq i\leq n-1 {\}}$, are used. This corrects previous misinterpretation

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

N-term Karatsuba Algorithm and its Application to Multiplier designs for Special Trinomials

In this paper, we propose a new type of non-recursive Mastrovito multiplier for $GF(2^m)$ using a $n$-term Karatsuba algorithm (KA), where $GF(2^m)$ is defined by an irreducible trinomial, $x^m+x^k+1, m=nk$. We show that such a type of trinomial combined with the $n$-term KA can fully exploit the spatial correlation of entries in related Mastrovito product matrices and lead to a low complexity architecture. The optimal parameter $n$ is further studied. As the main contribution of this study, the lower bound of the space complexity of our proposal is about $O(\frac{m^2}{2}+m^{3/2})$. Meanwhile, the time complexity matches the best Karatsuba multiplier known to date. To the best of our knowledge, it is the first time that Karatsuba-based multiplier has reached such a space complexity bound while maintaining relatively low time delay

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 Square-based Montgomery Multiplier for All Type C.1 Pentanomials

In this paper, we present a low complexity bit-parallel Montgomery multiplier for $GF(2^m)$ generated with a special class of irreducible pentanomials $x^m+x^{m-1}+x^k+x+1$. Based on a combination of generalized polynomial basis (GPB) squarer and a newly proposed square-based divide and conquer approach, we can partition field multiplications into a composition of sub-polynomial multiplications and Montgomery/GPB squarings, which have simpler architecture and thus can be implemented efficiently. Consequently, the proposed multiplier roughly saves 1/4 logic gates compared with the fastest multipliers, while the time complexity matches previous multipliers using divide and conquer algorithms

Formal Analysis of Arithmetic Circuits using Computer Algebra - Verification, Abstraction and Reverse Engineering

Despite a considerable progress in verification and abstraction of random and control logic, advances in formal verification of arithmetic designs have been lagging. This can be attributed mostly to the difficulty in an efficient modeling of arithmetic circuits and datapaths without resorting to computationally expensive Boolean methods, such as Binary Decision Diagrams (BDDs) and Boolean Satisfiability (SAT), that require “bit blasting”, i.e., flattening the design to a bit-level netlist. Approaches that rely on computer algebra and Satisfiability Modulo Theories (SMT) methods are either too abstract to handle the bit-level nature of arithmetic designs or require solving computationally expensive decision or satisfiability problems. The work proposed in this thesis aims at overcoming the limitations of analyzing arithmetic circuits, specifically at the post-synthesized phase. It addresses the verification, abstraction and reverse engineering problems of arithmetic circuits at an algebraic level, treating an arithmetic circuit and its specification as a properly constructed algebraic system. The proposed technique solves these problems by function extraction, i.e., by deriving arithmetic function computed by the circuit from its low-level circuit implementation using computer algebraic rewriting technique. The proposed techniques work on large integer arithmetic circuits and finite field arithmetic circuits, up to 512-bit wide containing millions of logic gates

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

Fast hybrid Karatsuba multiplier for Type II pentanomials

We continue the study of Mastrovito form of Karatsuba multipliers under the shifted polynomial basis (SPB), recently introduced by Li et al. (IEEE TC (2017)). A Mastrovito-Karatsuba (MK) multiplier utilizes the Karatsuba algorithm (KA) to optimize polynomial multiplication and the Mastrovito approach to combine it with the modular reduction. The authors developed a MK multiplier for all trinomials, which obtain a better space and time trade-off compared with previous non-recursive Karatsuba counterparts. Based on this work, we make two types of contributions in our paper. FORMULATION. We derive a new modular reduction formulation for constructing Mastrovito matrix associated with Type II pentanomial. This formula can also be applied to other special type of pentanomials, e.g. Type I pentanomial and Type C.1 pentanomial. Through related formulations, we demonstrate that Type I pentanomial is less efficient than Type II one because of a more complicated modular reduction under the same SPB; conversely, Type C.1 pentanomial is as good as Type II pentanomial under an alternative generalized polynomial basis (GPB). EXTENSION. We introduce a new MK multiplier for Type II pentanomial. It is shown that our proposal is only one $T_X$ slower than the fastest bit-parallel multipliers for Type II pentanomial, but its space complexity is roughly 3/4 of those schemes, where $T_X$ is the delay of one 2-input XOR gate. To the best of our knowledge, it is the first time for hybrid multiplier to achieve such a time delay bound

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

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