Large substitution boxes with efficient combinational implementations

At a fundamental level, the security of symmetric key cryptosystems ties back to Claude Shannon\u27s properties of confusion and diffusion. Confusion can be defined as the complexity of the relationship between the secret key and ciphertext, and diffusion can be defined as the degree to which the influence of a single input plaintext bit is spread throughout the resulting ciphertext. In constructions of symmetric key cryptographic primitives, confusion and diffusion are commonly realized with the application of nonlinear and linear operations, respectively. The Substitution-Permutation Network design is one such popular construction adopted by the Advanced Encryption Standard, among other block ciphers, which employs substitution boxes, or S-boxes, for nonlinear behavior. As a result, much research has been devoted to improving the cryptographic strength and implementation efficiency of S-boxes so as to prohibit cryptanalysis attacks that exploit weak constructions and enable fast and area-efficient hardware implementations on a variety of platforms. To date, most published and standardized S-boxes are bijective functions on elements of 4 or 8 bits. In this work, we explore the cryptographic properties and implementations of 8 and 16 bit S-boxes. We study the strength of these S-boxes in the context of Boolean functions and investigate area-optimized combinational hardware implementations. We then present a variety of new 8 and 16 bit S-boxes that have ideal cryptographic properties and enable low-area combinational implementations

Optimization of the scalar complexity of Chudnovsky2^2 multiplication algorithms in finite fields

We propose several constructions for the original multiplication algorithm of D.V. and G.V. Chudnovsky in order to improve its scalar complexity. We highlight the set of generic strategies who underlay the optimization of the scalar complexity, according to parameterizable criteria. As an example, we apply this analysis to the construction of type elliptic Chudnovsky$^2$ multiplication algorithms for small extensions. As a case study, we significantly improve the Baum-Shokrollahi construction for multiplication in $\mathbb F_{256}/\mathbb F_4$.Comment: 25 pages, 0 figur

Look-up the Rainbow: Efficient Table-based Parallel Implementation of Rainbow Signature on 64-bit ARMv8 Processors

Rainbow signature is one of the finalist in National Institute of Standards and Technology (NIST) standardization. It is also the only signature candidate that is designed based on multivariate quadratic hard problem. Rainbow signature is known to have very small signature size compared to other post-quantum candidates. In this paper, we propose an efficient implementation technique to improve performance of Rainbow signature schemes. A parallel polynomial-multiplication on a 64-bit ARMv8 processor was proposed, wherein a look-up table was created by pre-calculating the $4\times4$ multiplication results. This technique was developed based on the observation that the existing implementation of Rainbow\u27s polynomial-multiplication relies on the Karatsuba algorithm. It is not optimal due to the divide and conquer steps involved, whereby operations on $\mathbb{F}_{16}$ are divided into many small sub-fields of $\mathbb{F}_{4}$ and $\mathbb{F}_{2}$. Further investigations reveal that when the polynomial-multiplication in Rainbow signature is operated on $\mathbb{F}_{16}$, its operand is in 4-bit. Since the maximum combinations of a $4 \times 4$ multiplication is only 256, we constructed a 256-byte look-up table. According to the 4-bit constant, only 16-byte is loaded from the table at one time. The time-consuming multiplication is replaced by performing the table look-up. In addition, it calculates up-to 16 result values per register using characteristics of vector registers available on 64-bit ARMv8 processor. With the proposed fast polynomial-multiplication technique, we implemented the optimized Rainbow III and V. These two parameter sets are performed on $\mathbb{F}_{256}$, but they use sub-field $\mathbb{F}_{16}$ in the multiplication process. Therefore, the sub-field multiplication can be replaced with the proposed table look-up technique, which in turn omitted a significant number of operations. We have carried out the experiments on the Apple M1 processor, which shows up to 167.2$\times$ and 51.6$\times$ better performance enhancement at multiplier, and Rainbow signatures, respectively, compared to the previous implementation

On the tensor rank of multiplication in any extension of \F_2

In this paper, we obtain new bounds for the tensor rank of multiplication in any extension of \F_2. In particular, it also enables us to obtain the best known asymptotic bound. In this aim, we use the generalized algorithm of type Chudnovsky with derivative evaluations on places of degree one, two and four applied on the descent over \F_2 of a Garcia-Stichtenoth tower of algebraic function fields defined over \F_{2^4}

On the construction of elliptic Chudnovsky-type algorithms for multiplication in large extensions of finite fields

International audienceWe indicate a strategy in order to construct bilinear multiplication algorithms of type Chudnovsky in large extensions of any finite field. In particular, using the symmetric version of the generalization of Randriambololona specialized on the elliptic curves, we show that it is possible to construct such algorithms with low bilinear complexity. More precisely, if we only consider the Chudnovsky-type algorithms of type symmetric elliptic, we show that the symmetric bilinear complexity of these algorithms is in O(n(2q)^log * q (n)) where n corresponds to the extension degree, and log * q (n) is the iterated logarithm. Moreover, we show that the construction of such algorithms can be done in time polynomial in n. Finally, applying this method we present the effective construction, step by step, of such an algorithm of multiplication in the finite field F 3^57. Index Terms Multiplication algorithm, bilinear complexity, elliptic function field, interpolation on algebraic curve, finite field