A Novel code-based public-key encryption using semi-MDPC codes

Abstract BIKE is a post-quantum public-key encryption scheme based on Moderate-Density Parity-Check (MDPC) codes, gaining significant attention for its small public key and ciphertext sizes. However, it suffers from several critical limitations, including the lack of precise theoretical bounds for estimating the Decryption Failure Rate (DFR) and its vulnerability to weak-key and near-codeword attacks. These shortcomings ultimately contributed to its failure to be selected for standardization. To address these challenges, we propose an enhanced variant of the BIKE cryptosystem based on semi-MDPC codes. We reduce the syndrome decoding problem for semi-MDPC codes to the Quasi-Cyclic Codeword Finding and Quasi-Cyclic Syndrome Decoding problems. The proposed scheme resists major attacks specific to BIKE, such as weak-key and near-codeword attacks, while also enabling a rigorous theoretical analysis of the DFR with provable upper bounds–significantly improving security and reliability. Furthermore, we introduce a block-cyclic matrix structure to enhance security and reduce ciphertext size at the cost of an increased public key size. Compared with McEliece, our scheme achieves significantly smaller key sizes. Against the standardized HQC scheme, while the public key is approximately twice as large, the ciphertext size is reduced by about 50%, offering superior storage efficiency in ciphertext-constrained environments.

Authors

Institutions

Publication Details

Journal
Cybersecurity
Published
2026-04-17
DOI
https://doi.org/10.1186/s42400-026-00576-5
Primary Topic
Coding theory and cryptography
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel code-based public-key encryption using semi-MDPC codes

L Chen
Cybersecurity
Coding theory and cryptography
article

A Novel code-based public-key encryption using semi-MDPC codes

L Chen
article en

Abstract

Abstract BIKE is a post-quantum public-key encryption scheme based on Moderate-Density Parity-Check (MDPC) codes, gaining significant attention for its small public key and ciphertext sizes. However, it suffers from several critical limitations, including the lack of precise theoretical bounds for estimating the Decryption Failure Rate (DFR) and its vulnerability to weak-key and near-codeword attacks. These shortcomings ultimately contributed to its failure to be selected for standardization. To address these challenges, we propose an enhanced variant of the BIKE cryptosystem based on semi-MDPC codes. We reduce the syndrome decoding problem for semi-MDPC codes to the Quasi-Cyclic Codeword Finding and Quasi-Cyclic Syndrome Decoding problems. The proposed scheme resists major attacks specific to BIKE, such as weak-key and near-codeword attacks, while also enabling a rigorous theoretical analysis of the DFR with provable upper bounds–significantly improving security and reliability. Furthermore, we introduce a block-cyclic matrix structure to enhance security and reduce ciphertext size at the cost of an increased public key size. Compared with McEliece, our scheme achieves significantly smaller key sizes. Against the standardized HQC scheme, while the public key is approximately twice as large, the ciphertext size is reduced by about 50%, offering superior storage efficiency in ciphertext-constrained environments.

CybersecurityVol. 9(1)
Nankai University (CN)
National Key Research and Development Program of China
Peace, Justice and strong institutions
Openalex Percentile: Top 20%
Coding theory and cryptography
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.