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Symmetric random function generator (SRFG): A novel cryptographic primitive for designing fast and robust algorithms

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  • Saha, Rahul
  • G, Geetha

Abstract

Cryptanalysis analyses various combinations among plaintexts, ciphertexts and random keys; even using differential methods or analog methods, the attackers can interpret the keys depending upon the operations in the round functions or any subset of the algorithm. The previous research emphasizes on creation of different cryptographic functions, however the randomness of such functions has not been researched significantly so far. In this paper, we have shown a random function generator which can be used for any cryptographic algorithm. This generator outputs the combination of functions in random and cannot be traced back due its randomness. The objective of our research work is not to identify a particular boolean function that is balanced or symmetric based on its input variables, our proposed work provides a random combination of generic boolean functions as used in MD5 or SHA series, block cipher round functions and stream ciphers. Moreover, the random selection of input variables for a particular function also makes it desirable for cryptographic function modules. The results of our experimentation show that the functions generated by the proposed generator provide a good non-linearity, resiliency and balanced effect.

Suggested Citation

  • Saha, Rahul & G, Geetha, 2017. "Symmetric random function generator (SRFG): A novel cryptographic primitive for designing fast and robust algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 371-377.
  • Handle: RePEc:eee:chsofr:v:104:y:2017:i:c:p:371-377
    DOI: 10.1016/j.chaos.2017.08.020
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    References listed on IDEAS

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    1. Çavuşoğlu, Ünal & Kaçar, Sezgin & Pehlivan, Ihsan & Zengin, Ahmet, 2017. "Secure image encryption algorithm design using a novel chaos based S-Box," Chaos, Solitons & Fractals, Elsevier, vol. 95(C), pages 92-101.
    2. Sun, Fuyan & Liu, Shutang, 2009. "Cryptographic pseudo-random sequence from the spatial chaotic map," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2216-2219.
    3. Hu, Yue & Liao, Xiaofeng & Wong, Kwok-wo & Zhou, Qing, 2009. "A true random number generator based on mouse movement and chaotic cryptography," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2286-2293.
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    Cited by:

    1. Nepomuceno, Erivelton G. & Lima, Arthur M. & Arias-García, Janier & Perc, Matjaž & Repnik, Robert, 2019. "Minimal digital chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 62-66.

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