Cumulatively All-Lossy-But-One Trapdoor Functions from Standard Assumptions - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2022

Cumulatively All-Lossy-But-One Trapdoor Functions from Standard Assumptions


Chakraborty, Prabhakaran, and Wichs (PKC'20) recently introduced a new tag-based variant of lossy trapdoor functions, termed cumulatively all-lossy-but-one trapdoor functions (CALBO-TDFs). Informally, CALBO-TDFs allow defining a public tag-based function with a (computationally hidden) special tag, such that the function is lossy for all tags except when the special secret tag is used. In the latter case, the function becomes injective and efficiently invertible using a secret trapdoor. This notion has been used to obtain advanced constructions of signatures with strong guarantees against leakage and tampering, and also by Dodis, Vaikunthanathan, and Wichs (EUROCRYPT'20) to obtain constructions of randomness extractors with extractor-dependent sources. While these applications are motivated by practical considerations, the only known instantiation of CALBO-TDFs so far relies on the existence of indistinguishability obfuscation. In this paper, we propose the first two instantiations of CALBO-TDFs based on standard assumptions. Our constructions are based on the LWE assumption with a sub-exponential approximation factor and on the DCR assumption, respectively, and circumvent the use of indistinguishability obfuscation by relying on lossy modes and trapdoor mechanisms enabled by these assumptions.
Fichier principal
Vignette du fichier
calbo-final.pdf (586.98 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03820072 , version 1 (18-10-2022)


  • HAL Id : hal-03820072 , version 1


Benoît Libert, Ky Nguyen, Alain Passelègue. Cumulatively All-Lossy-But-One Trapdoor Functions from Standard Assumptions. SCN 2022 - Proceedings of the 13th Conference on Security in Communication Networks, Sep 2022, Amalfi, Italy. ⟨hal-03820072⟩
48 View
45 Download


Gmail Facebook X LinkedIn More