Groestlcoin (GRS) Coin Review : It Is Good Or Bad Review

About Groestlcoin (GRS) Coin

Groestlcoin (GRS) Coin hash function Grøstl was designed in 2008 as a candidate for the SHA-3 competition [18], organized by the National Institute of Standards and Technology (NIST). In 2010, Grøstl was selected as one of five finalists in the competition. Grøstl borrows components from the AES block cipher, which became a United States federal government standard in 2001 [17]. The AES is known for its good performance on a wide variety of platforms, which is due to a large amount of flexibility in the choice of implementation methods. Recently, Intel introduced an instruction set extension for computing AES rounds [9], which makes encryption using the AES on CPUs implementing this instruction set very efficient.

Groestlcoin (GRS) Coin Although several underlying components in Grøstl differ from the ones used in the AES, Grøstl still enjoys many of the same implementation benefits as the AES. Even the AES instruction set extension can be used to significantly speed up Grøstl. In this paper, we describe various software implementation techniques for Grøstl suitable for platforms ranging from 8-bit microcontrollers to processors with SIMD and AES instruction set extensions. All these implementations can be downloaded from http://www.groestl.info/

Groestlcoin (GRS) Coin hash function iterates an underlying compression function in a variant of the Merkle-Damg˚ard construction [7, 15], where the size of the state (or chaining value) passed on from one iteration to the next is at least twice as large as the final hash value. The final hash value is computed from the last chaining value using an output transformation. Hence, Grøstl is known as a wide pipe design. The compression function and the output transformation are based on permutations using round transformations similar to those of the AES [16].

Groestlcoin (GRS) Storage Key Points

The Hash Function

Groestlcoin (GRS) comes in several variants with different output sizes. The denote by n the number of bits in the output, and the variant returning n bits is denoted Grøstl-n. Here, we focus on Grøstl-256 and Grøstl512. Variants returning less than 256 bits differ from Grøstl-256 only in the initial value and in the final truncation to produce the hash value. Similarly, variants returning more than 256 bits differ from Grøstl-512 in the same two respects. The input message M is padded and split into blocks M1, M2, . . . , Mt of bits with = 512 for Grøstl256, and = 1024 for Grøstl-512. The initial value IV , the intermediate hash values Hi , and the permutations P and Q are of size bits as well. (The exact definition of the IV can be found in [8]). The message blocks are processed via the compression function f(Hi−1, Mi), which accepts two -bit inputs and outputs an-bit value.

The Output Transformation

Groestlcoin (GRS) After the last call to the compression function, an output transformation Ω is applied to Ht to give the final hash value of size n: Ω(Ht) = truncn(P(Ht) ⊕ Ht), where truncn(x) discards all but the least significant n bits of x. The output transformation is also shown in Figure 2

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Byte Slice Implementation

Groestlcoin (GRS) Another option to implement Grøstl is a byte-wise parallel computation of columns. All round transformations except ShiftBytes and AddRoundConstant apply exactly the same computation to each column of the Grøstl state independently. Therefore, we can use a Single Instruction Multiple Data (SIMD) approach to compute these identical operations on more than one column at the same time. We call this a byte slice implementation [1] since the Grøstl state is cut into column slices of bytes. The state is stored in row ordering. Using w-bit registers, w/8 columns can be computed in parallel (see Figure 9). This approach is most efficient for small (8-bit) and large register sizes (128-bit and more). A requirement for this approach to be efficient is that all round transformations of Grøstl can be parallelised using only a few w-bit SIMD instructions. AddRoundConstant and MixBytes can be computed in parallel simply using basic ALU instructions. For ShiftBytes we need a byte shuffling instruction or some mask and rotate instructions. The most difficult round transformation to parallelise is the 8-bit table lookup of SubBytes.

Implementing Grøstl Round Transformations

In this Section we list common techniques to efficiently implement the individual Grøstl round transformations. The listed techniques can be used on various platforms using different word sizes, as well as in hardware and in software. In most cases also special optimization techniques which combine round transformations may lead to better results on some platforms (also see Sections 5, 3.2 and 3.3)

Add Round Constant

Groestlcoin (GRS) AddRoundConstant transformation consists of XORs of bytes in the state with constants. In most cases, these constants will be stored using the same data structures and ordering conventions as the state itself, in which case the XORs are simply carried out word by word. One may exploit the fact that the constants used in Q correspond to a complementation of each byte, followed by an XOR with the same constants as those used in P. Note, however, that in Q, these constants are XORed to the bottom row instead of the top row (as in P).

Table-based Implementation

The most efficient way to implement MixBytes is using precomputed T-tables (also see Section 5). Especially since in this case, the table lookups for MixBytes can also be combined with those of the S-box. In the T-table approach, the effect of each state byte on one column (8 bytes) is precomputed and stored in a table of 256 64-bit entries. For each input byte of one column, we need a separate table. Then, e.g. the first column can be computed as follows: