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dc.contributor.authorBudaghyan, Lilya
dc.contributor.authorCarlet, Claude
dc.contributor.authorHelleseth, Tor
dc.contributor.authorKaleyski, Nikolay Stoyanov
dc.date.accessioned2021-05-27T13:07:55Z
dc.date.available2021-05-27T13:07:55Z
dc.date.created2021-01-19T11:19:50Z
dc.date.issued2020
dc.PublishedIEEE Transactions on Information Theory. 2020, 66 (9), 5742-5753.
dc.identifier.issn0018-9448
dc.identifier.urihttps://hdl.handle.net/11250/2756701
dc.description.abstractWe investigate the differential properties of a vectorial Boolean function G obtained by modifying an APN function F . This generalizes previous constructions where a function is modified at a few points. We characterize the APN-ness of G via the derivatives of F, and deduce an algorithm for searching for APN functions whose values differ from those of F only on a given set U ⊆ F 2n . We introduce a value Π F associated with any F, which is invariant under CCZ-equivalence. We express a lower bound on the distance between a given APN function F and the closest APN function in terms of Π F . We show how Π F can be computed efficiently for F quadratic. We compute Π F for all known APN functions over F 2n . up to n ≤ 8. his is the first new CCZ-invariant for APN functions to be introduced within the last ten years. We derive a mathematical formula for this lower bound for the Gold function F (x) = x 3 , and observe that it tends to infinity with n. Finally, we describe how to efficiently find all sets U such that, taking G(x) = F (x) + v for x ∈ U and G(x) = F (x) for x ∉ U,G(x) is APN.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.titleOn the Distance Between APN Functionsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holderCopyright 2020 IEEEen_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.doihttps://doi.org/10.1109/TIT.2020.2983684
dc.identifier.cristin1874120
dc.source.journalIEEE Transactions on Information Theoryen_US
dc.source.4066
dc.source.149
dc.source.pagenumber5742-5753en_US
dc.identifier.citationIEEE Transactions on Information Theory. 2020, 66(9), 5742-5753en_US
dc.source.volume66en_US
dc.source.issue9en_US


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