This repository contains Python code and data for the paper: Optimizing Linear Correctors: A Tight Output Min-Entropy Bound and Selection Technique, published in IEEE Transactions on Information Forensics and Security (authors' version, journal version )
The directory Code/
contains necessary Python code to reproduce figures from the paper. All figures can be generated directly from main.py. The content of parameters.py can be modified to speed up the code execution by lowering Decimal
context precision, setting another output min-entropy lower bound or to modify the parameters of the bisection method.
- NBC_set: List with parameters and weight distributions of binary linear codes that are used to calculate the new bound of the corresponding correctors (NBC set) - ZIP file
- NBCCYC_set: List with parameters and weight distributions of cyclic binary linear codes that are used to calculate the new bound of the corresponding correctors (NBCCYC set)
- OBC_set: List with parameters of binary linear codes that are used to calculate the old bound of the corresponding correctors (OBC set)
- OBCCYC_set: List with parameters of cyclic binary linear codes that are used to calculate the old bound of the corresponding correctors (OBCCYC set)
- Optimal_NBC: Optimal correctors for output min-entropy rate of 0.999 according to the new bound
- Optimal_NBCCYC: Optimal correctors for output min-entropy rate of 0.999 based only on the cyclic codes according to the new bound
- Optimal_OBC: Optimal correctors for output min-entropy rate of 0.999 according to the old bound
- Optimal_OBCCYC: Optimal correctors for output min-entropy rate of 0.999 based only on the cyclic codes according to the old bound
- Optimal_Area_NBCCYC: Optimal correctors according to throughput, code rate and area (GEs for NanGate 45nm standard-cell library) for output min-entropy rate of 0.999 based only on the cyclic codes according to the new bound
- Modified_generator_matrices_OBC_NBC: Modified generator matrices of the best known linear codes that originally contained one or multiple all-zero columns (BKLCs from M. Grassl, ''Bounds on the minimum distance of linear codes and quantum codes,'' Online available at: http://www.codetables.de) - ZIP file
Files 1 and 2 contain in each line:
- parameters of the code on which the corresponding corrector is based (
n
,k
,d
), - reference where the complete code description and/or its weight distribution can be found (
source
), - sequence of tuples which represents code's weight distribution (
Weight Distribution
), where the i-th tuple<w_i, a_i>
represents number of codewordsa_i
with weightw_i
, - in cases where MAGMA uses PRNG we additionally provide
MAGMA Seed
andMAGMA Seed iteration
values in brackets that were used for our constructions.
Files 3 and 4 contain in each line:
- parameters of the code on which the corresponding corrector is based (
n
,k
,d
), - reference where the complete code description can be found (
source
).
Files 5, 6, 7, 8 and 9 contain in each line:
- parameters of the code on which the corresponding corrector is based (
n
,k
,d
), - minimum required min-entropy of the input raw bits to achieve the output min-entropy rate of 0.999 (
H_in_req
), - code rate = throughput reduction (
CR
), - efficiency of the corrector at H_in_req (
efficiency
), - only for File 9: area estimation (in GEs for NanGate 45nm standard-cell library) occupied by the corrector (
area
) when implemented using generator or parity-check polynomial (construction
).
File 10 contains:
- parameters of the code on which the corresponding corrector is based (
n
,k
,d
), - in cases where MAGMA uses PRNG we additionally provide
MAGMA Seed
andMAGMA Seed iteration
values in brackets that were used for our constructions, - followed by
k
rows withn
entries of the code's generator matrix.
All constructions are based on binary linear codes whose descriptions can be found here:
- M. Grassl, ''Bounds on the minimum distance of linear codes and quantum codes,'' Online available at: http://www.codetables.de.
- M. Terada, J. Asatani, and T. Koumoto, ''Weight Distribution,'' Online available at: https://isec.ec.okayama-u.ac.jp/home/kusaka/wd/index.html.
- N. J. Sloane, ''List of weight distributions in the on-line encyclopedia of integer sequences,'' Online available at: https://oeis.org/wiki/List_of_weight_distributions.
- S. Lin and D. J. Costello, ''Error Control Coding: Fundamentals and Applications,'' Pearson-Prentice Hall, 2004.
- D. Schomaker and M. Wirtz, ''On binary cyclic codes of odd lengths from 101 to 127,'' IEEE Transactions on Information Theory, vol. 38, no. 2, pp. 516–518, 1992.
- T. Sugita, T. Kasami, and T. Fujiwara, ''The weight distribution of the third-order Reed-Muller code of length 512,'' IEEE Transactions on Information Theory, vol. 42, no. 5, pp. 1622–1625, Sep. 1996.
- Y. Desaki, T. Fujiwara, and T. Kasami, ''The weight distributions of extended binary primitive BCH codes of length 128,'' IEEE Transactions on Information Theory, vol. 43, no. 4, pp. 1364–1371, 1997.
- T. Fujiwara and T. Kasami, ''The weight distribution of (256, k) extended binary primitive BCH code with k<= 63, k>= 207,'' IEICE, IT97, Technical Report, 1993.
- T.-K. Truong, Y. Chang, and C.-D. Lee, ''The weight distributions of some binary quadratic residue codes,'' IEEE Transactions on Information Theory, vol. 51, no. 5, pp. 1776–1782, 2005.
- M. Tomlinson, C. J. Tjhai, M. A. Ambroze, M. Ahmed, and M. Jibril, ''Error-Correction Coding and Decoding: Bounds, Codes, Decoders, Analysis and Applications,'' Springer Nature, 2017.
@article{Grujic2023OptLinCor,
author={Gruji\'{c}, Milo\v{s} and Verbauwhede, Ingrid},
journal={IEEE Transactions on Information Forensics and Security},
title={Optimizing Linear Correctors: A Tight Output Min-Entropy Bound and Selection Technique},
year={2024},
volume={19},
number={},
pages={586-600},
doi={10.1109/TIFS.2023.3326986}
}
For more details on the new bound and selection procedure, please consult the paper or contact the authors: [email protected], [email protected]