Quantum computing presents a major risk to traditional public-key cryptosystems, accelerating the transition toward Post-Quantum Cryptography (PQC). The Hamming Quasi-Cyclic (HQC) Key Encapsulation Mechanism (KEM) is a code-based PQC candidate selected by the National Institute of Standards and Technology (NIST) that offers strong security guarantees based on the hardness of syndrome decoding.
However, its large public keys, ciphertext sizes, and computational overhead restrict its practical implementation in environments with limited bandwidth and resources.
Table of Contents
I. INTRODUCTION
II. LITERATURE REVIEW
A. Introduction and Problem Statement
B. Code-Based Cryptography and HQC
C. Performance and Deployment Challenges of HQC
D. Parameter Reduction and Security Trade-offs
E. RMRS Concatenated Codes as a Potential Solution
F. Synthesis and Justification
G. Methods to be used
III. TEST CONFIGURATION:
A. Methodology Experimentation and Environment
B. Specification of Hardware and System Architecture
C. Software Framework: Liboqs and PQClean
D. Benchmarking and Data Collection
E. Logical Diagram
F. Discussion of Results and Analysis:
G. Real-Time Monitoring and Optimization
H. Data Integrity and Validation
I. Security-Performance Trade-off Analysis
IV. FUTURE WORK
Research Objectives and Themes
The primary objective of this research is to optimize the Hamming Quasi-Cyclic (HQC) key encapsulation mechanism by reducing key and ciphertext sizes without compromising post-quantum security. The study addresses the computational and memory bottlenecks associated with standard HQC configurations in resource-constrained environments like IoT devices by employing RMRS concatenated codes and advanced hardware-accelerated decoding.
- Reduction of public key and ciphertext sizes to enhance communication efficiency.
- Improvement of computational performance via optimized parameter tuning.
- Restoration of NIST Level 1 security using Guruswami-Sudan (GS) list decoding.
- Hardware-level acceleration using AVX2 and AES-NI instructions.
- Empirical validation through cycle-precise RDTSC profiling.
Excerpt from the Book
Performance and Deployment Challenges of HQC
Alagic et al. (2020) point out that despite the conservative and well-understood security guarantees of code-based schemes, key sizes are large enough to impose severe bottlenecks in[1] IoT security protocols Embedded Hardware Implementation, Mobile and wireless communications, Handshakes in TLS in the internet infrastructure.
In the same manner, Bernstein et al. (2019) state that code based cryptography is one of the most reliable methods in PQC, but it cannot be used in large volumes due to too large memory and bandwidth consumption[2].
The two works come to the same conclusion, namely, in order to implement HQC in practice, a reduction in the size of key and ciphertext is necessary, although it is necessary to perform a careful analysis to avoid compromising the security [1][2].
Summary of Chapters
I. INTRODUCTION: Outlines the threat posed by quantum computing to traditional cryptography and presents the HQC scheme as a resilient, code-based post-quantum alternative.
II. LITERATURE REVIEW: Analyzes the existing research on HQC, focusing on the trade-offs between parameter reduction for efficiency and the maintenance of security levels.
III. TEST CONFIGURATION:: Details the experimental design, including the use of liboqs, benchmarking methodologies, and the hardware environment used to evaluate the optimized HQC variant.
IV. FUTURE WORK: Discusses potential directions such as porting vectorized operations to ARM/RISC-V architectures and conducting formal Side-Channel Analysis.
Keywords
Post-Quantum Cryptography, HQC, Hamming Quasi-Cyclic, Key Encapsulation Mechanism, RMRS, Parameter Reduction, Guruswami-Sudan, AVX2, NIST, Syndrome Decoding, Computational Efficiency, Latency, IoT, Cryptographic Security, Benchmarking.
Frequently Asked Questions
What is the primary focus of this research?
The research focuses on optimizing the HQC key encapsulation mechanism to reduce key size and computational latency, making it more suitable for resource-limited environments like IoT devices.
Which specific cryptographic schemes are discussed?
The work primarily discusses Hamming Quasi-Cyclic (HQC) as a code-based PQC candidate, comparing its performance against lattice-based schemes like Kyber.
What is the main goal or research question?
The goal is to determine if systematic parameter tuning and the use of RMRS concatenated codes can improve HQC performance without compromising its underlying security assumptions.
Which scientific methods were employed?
The study utilizes a quantitative experimental research design, employing RDTSC cycle-precise profiling, liboqs framework benchmarking, and hardware acceleration via AVX2 and AES-NI.
What does the main body cover?
It covers literature review, experimental setup, integration of Guruswami-Sudan list decoding, and empirical analysis of performance metrics like communication overhead and latency reduction.
What are the characterizing keywords of this work?
Key terms include Post-Quantum Cryptography, HQC, parameter reduction, Guruswami-Sudan list decoding, and performance optimization.
How did the research address the potential security degradation from parameter reduction?
By implementing Guruswami-Sudan list decoding, which increased the error-correction radius, the researchers were able to restore the security workfactor to the NIST 128-bit threshold.
What role does hardware acceleration play in the optimization?
Hardware acceleration, specifically AVX2 and 256-bit YMM registers, was critical to mitigate the computational complexity introduced by the Guruswami-Sudan list decoding process.
- Quote paper
- Parichay Dey (Author), 2026, Evaluating the Impact of Key Size Reduction on the Security of the HQC Post-Quantum Cryptosystem using RMRS, Munich, GRIN Verlag, https://www.grin.com/document/1728476
