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Finding efficient nonlinear functions by means of genetic programming

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URI: https://hdl.handle.net/10016/4092
ISSN: 1611-3349 (Online)
ISBN: 978-3-540-40803-1
DOI: 10.1007/b12002
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finding-efficient_LNCS_2003_ps.pdf (346.81 KB)
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2003-09
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Springer
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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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7th International Conference, KES 2003. Proceedings, Part I. Oxford, UK, September 3-5, 2003
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Knowledge-Based Intelligent Information and Engineering Systems. Berlin: Springer, 2003. P. 1192-1198 (Lecture Notes in Computer Science; 2773)
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