Andreeva, E., & Weninger, A. (2023). A Forkcipher-Based Pseudo-Random Number Generator. In M. Tibouchi & X. Wang (Eds.), Applied Cryptography and Network Security (pp. 3–31). https://doi.org/10.1007/978-3-031-33491-7_1
forkcipher; pseudo-random number generator; provable security
en
Abstract:
Good randomness is needed for most cryptographic appli-
cations. In practice pseudo-random number generators (PRNGs) are
employed. CTR_DRBG is a popular choice and among the recommended
PRNGs by NIST. It is defined for use with primitives like AES or TDEA,
which are not always suited for lightweight applications.
In this work we propose FCRNG, a new PRNG, similar to CTR_DRBG, that
is optimized for the lightweight setting (e.g. the Internet of Things). Our
FCRNG construction utilizes the expanding and tweakable forkcipher prim-
itive instantiated with ForkSkinny, which was introduced by Andreeva et
al. at ASIACRYPT 2019. FCRNG employs internally a forkcipher-based
counter-style mode FCTR. We propose two FCTR variants: FCTR-c for opti-
mized speed and FCTR-T for optimized security. We then show that FCRNG
with ForkSkinny can be 33% faster than CTR_DRBG when instantiated with
the AES blockcipher. FCRNG achieves also a better security bound in the
robustness security game - first introduced by Dodis et al. at CCS’13 and
now the standard security goal for PRNGs. Contrary to the CRYPTO
2020 security bound by Hoang and Shen established for CTR_DRBG, the
security of our construction with FCTR-T does not degrade with the length
of the random inputs, nor the amount of requested output pseudoran-
dom bits. FCRNG passes all tests of the NIST test suite for pseudorandom
number generators.
