A Note on Vectorial Boolean Functions as Embeddings
Augustine Musukwa, Massimiliano Sala

TL;DR
This paper investigates the properties of vectorial Boolean functions as embeddings, analyzing their component functions, and establishing bounds on balanced components, with implications for cryptographic functions.
Contribution
It provides new bounds on the number of balanced components in embeddings and explores properties of partially-bent embeddings, linking to APN functions.
Findings
At most 2^m - 2^{m-n} components of an embedding can be balanced.
Partially-bent embeddings have at least 2^n - 1 balanced components when n is even.
A relation between embeddings and APN functions is established.
Abstract
Let be a vectorial Boolean function from to , with . We define as an embedding if is injective. In this paper, we examine the component functions of , focusing on constant and balanced components. Our findings reveal that at most components of can be balanced, and this maximum is achieved precisely when is an embedding, with the remaining components being constants. Additionally, for partially-bent embeddings, we demonstrate that there are always at least balanced components when is even, and balanced components when is odd. A relation with APN functions is shown.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputability, Logic, AI Algorithms
