A Systematic Review of Graph-Theoretic Approaches to Post-Quantum Cryptographic Protocols: Methods, Architectures, and Future Research Directions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The rapid advancement of quantum computing poses a significant threat to classical cryptographic systems, necessitating the development of robust post-quantum cryptographic (PQC) protocols. Among emerging approaches, graph-theoretic techniques have gained prominence due to their computational hardness, structural flexibility, and applicability in designing secure cryptographic primitives. This paper presents a systematic review of graph-theoretic approaches to post-quantum cryptographic protocols, focusing on methods, architectures, and future research directions. The study analyzes recent developments from 2018 to 2025, examining how graph-based constructs such as expander graphs, isogeny graphs, lattice graphs, and combinatorial structures contribute to secure key exchange, encryption, and authentication mechanisms. Additionally, the integration of chaotic systems and generative artificial intelligence is explored to enhance entropy generation and adaptive security mechanisms. The review identifies key trends, including hybrid graph-chaotic models, optimization of graph traversal algorithms for cryptographic efficiency, and AI-assisted cryptanalysis resistance. Contributions of this work include a structured synthesis of 30 studies, identification of research gaps in scalability and standardization, and a comprehensive evaluation of graph-theoretic PQC within secure software engineering frameworks. The findings emphasize the potential of graph-based cryptography as a resilient paradigm in the quantum era while highlighting the need for further interdisciplinary research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it