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On the normality of p-ary bent functions
Wilfried Meidl1,2, Ísabel Pirsic3
11Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences, Linz, Austria.
Researchers developed a new algorithm to test the normality of p-ary bent functions. This algorithm identified bent functions that deviate from expected bounds, leading to new examples in infinitely many dimensions.
Area of Science:
- Cryptography
- Abstract Algebra
- Number Theory
Background:
- Bent functions are crucial in cryptography, particularly in constructing secure systems.
- Understanding the structure of bent functions, specifically their normality, is key to analyzing their cryptographic properties.
- Existing research shows many Boolean and p-ary bent functions exhibit a high degree of normality, often being affine on large subspaces.
Purpose of the Study:
- To develop a general algorithm for testing the normality of p-ary bent functions.
- To investigate whether p-ary bent functions can deviate from the established bounds on their normality.
- To construct new classes of bent functions with specific normality properties.
Main Methods:
- Development of a novel algorithm to test the normality of functions from F_p^n to F_p.
- Application of the algorithm to analyze specific p-ary bent functions in small dimensions.
- Utilizing the direct sum construction to generate bent functions with novel properties.
Main Results:
- The study demonstrates that not all p-ary bent functions adhere to the theoretical bounds on normality.
- The developed algorithm successfully identified bent functions that are not affine on subspaces up to the expected maximal dimension.
- New examples of p-ary bent functions exhibiting lower normality were constructed, extending to infinitely many dimensions.
Conclusions:
- The findings challenge the assumption that most p-ary bent functions are highly normal.
- The new algorithm provides a valuable tool for further cryptanalysis and the design of cryptographic primitives.
- The discovery of bent functions with different normality behaviors opens new avenues for research in coding theory and cryptography.
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