Abstract
The design of highly nonlinear functions is relevant for a number of different applications, ranging from database hashing to message authentication. But, apart from useful, it is quite a challenging task. In this work, we propose the use of genetic programming for finding functions that optimize a particular nonlinear criteria, the avalanche effect, using only very efficient operations, so that the resulting functions are extremely efficient both in hardware and in software.
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© 2003 Springer-Verlag Berlin Heidelberg
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Castro, J.C.H., Viñuela, P.I., del Arco-Calderón, C.L. (2003). Finding Efficient Nonlinear Functions by Means of Genetic Programming. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_161
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DOI: https://doi.org/10.1007/978-3-540-45224-9_161
Publisher Name: Springer, Berlin, Heidelberg
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