Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

A Study of Error Floor Behavior in QC-MDPC Codes

Published

Author(s)

Sarah Arpin, Tyler Billingsley, Daniel Hast, Jun Bo Lao, Ray Perlner, Angela Robinson

Abstract

We present experimental findings on the decoding failure rate (DFR) of BIKE, a third-round candidate in the NIST Post-Quantum Standardization process, at the 20-bit security level. We select parameters according to BIKE design principles and conduct a series of experiments. We directly compute the average DFR on a range of BIKE block sizes and identify the both the waterfall and error floor regions of the DFR curve. We then study the influence on the average DFR of three sets C, N , and 2N of near-codewords—vectors of low weight that induce syndromes of low weight—defined by Vasseur in 2021. We find that error vectors leading to decoding failures have small maximum support intersection with elements of these sets; further, the distribution of intersections is quite similar to that of sampling random error vectors and counting the intersections with C, N , and 2N . Our results indicate that these three sets are not sufficient in classifying vectors expected to cause decoding failures. Finally, we study the role of syndrome weight on the decoding behavior and conclude that the set of error vectors that lead to decoding failures differ from random vectors by having low syndrome weight.
Citation
IACR Eprint
Volume
2022

Keywords

BIKE, error-correcting codes, McEliece, PQC, QC-MDPC

Citation

Arpin, S. , Billingsley, T. , Hast, D. , Lao, J. , Perlner, R. and Robinson, A. (2022), A Study of Error Floor Behavior in QC-MDPC Codes, IACR Eprint, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935028, https://eprint.iacr.org/2022/1043 (Accessed November 23, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created August 17, 2022, Updated November 29, 2022