R-Hash: Hash Function Using Random Quadratic Polynomials Over GF(2)
In this paper researchers describe an improved version of HF-hash [7] viz. R-hash: Hash Function Using Random Quadratic Polynomials Over GF(2). The compression function of HF-hash consists of 32 polynomials with 64 variables over GF(2), which were taken from the first 32 polynomials of HFE challenge...
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| Veröffentlicht in: | International Journal of Computer Science and Information Technology 2012-12, Vol.4 (6), p.159-168 |
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| container_title | International Journal of Computer Science and Information Technology |
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| creator | Dey, Dhananjoy |
| description | In this paper researchers describe an improved version of HF-hash [7] viz. R-hash: Hash Function Using Random Quadratic Polynomials Over GF(2). The compression function of HF-hash consists of 32 polynomials with 64 variables over GF(2), which were taken from the first 32 polynomials of HFE challenge-1 by forcing last 16 variables as 0. The mode operation used in computing HF-hash was Merkle-Damgard. We have randomly selected 32 quadratic non-homogeneous polynomials having 64 variables over GF(2) in case of R-hash to improve the security of the compression function used in HF-hash. In designing R-hash, we have also changed the mode operation used in HF-hash, because of the theoretical weakness found in the Merkle-Damgard construction. In this paper researchers will prove that R-hash is more secure than HF-hash and SHA-256 as well as we will show that it is also faster than HF-hash. |
| doi_str_mv | 10.5121/ijcsit.2012.4612 |
| format | Article |
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| ispartof | International Journal of Computer Science and Information Technology, 2012-12, Vol.4 (6), p.159-168 |
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| source | EZB-FREE-00999 freely available EZB journals |
| subjects | Compressing Computer information security Construction Hafnium Hash based algorithms Information systems Mathematical analysis Mathematical models |
| title | R-Hash: Hash Function Using Random Quadratic Polynomials Over GF(2) |
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