Stringology Based Cryptology

• URL: http://arxiv.org/abs/2604.16669v1
• Date: Fri, 17 Apr 2026 19:58:56 GMT
• Title: Stringology Based Cryptology
• Abstract summary: This paper introduces the concept of Stringology-Based Cryptology.<n>It applies classical string processing and pattern matching techniques to analyze structural properties of cryptographic outputs.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The modern cryptographic primitives are known to generate large volumes of sequential data like keystreams, ciphertext blocks, and hash outputs. Traditional cryptgraphic evaluation methods rely primarily on statistical randomness tests and algebraic cryptanalysis techniques. This paper introduces the concept of Stringology-Based Cryptology (SBC), which applies classical string processing and pattern matching techniques to analyze structural properties of cryptographic outputs. By interpreting cryptographic outputs as symbolic sequences, stringology algorithms can be used to detect pattern recurrence, substring distributions, and structural correlations. In addition, the paper demonstrate how pattern frequency analysis and substring recurrence metrics can be applied to evaluate keystream outputs generated by stream ciphers. Experimental results illustrate that SBC analysis provides complementary insights into structural characteristics of cryptographic sequences and may support future research in structural cryptanalysis and cryptographic evaluation

Related papers

• Many Circuits, One Mechanism: Input Variation and Evaluation Granularity in Circuit Discovery [49.50794188352666]
  We show that structural differences between circuits are not sufficient evidence for distinct mechanisms.<n>Standard evaluation practice obscures this pattern, while edge-level evaluation reveals the many-to-one mapping from structure to function.
  arXiv  Detail & Related papers  (2026-06-04T15:10:14Z)
• Structural Analysis of Cryptographic Sequences using Stringology-Based Fingerprinting [0.0]
  We introduce a stringology-based fingerprinting, (SBF) framework for the structural analysis of cryptographic sequences.<n>The proposed SBF framework interprets cryptographic outputs as symbolic strings and applies pattern-based feature extraction to capture structural statistics.<n>The results demonstrate that stringology-based pattern analysis can reveal measurable structural signatures across different sequence sources.
  arXiv  Detail & Related papers  (2026-05-18T21:19:08Z)
• Neural Stringology Based Cryptanalysis of EChaCha20 [0.0]
  A Neural Stringology Cryptanalysis (NSC) framework combines classical string pattern analysis with machine learning techniques to investigate potential structural anomalies in stream cipher keystreams is introduced.<n>The proposed NSC framework can identify distinguishable structural characteristics in the keystream data under controlled conditions.
  arXiv  Detail & Related papers  (2026-04-14T20:33:42Z)
• Intermittent File Encryption in Ransomware: Measurement, Modeling, and Detection [0.32622301272834514]
  This paper provides a systematic empirical characterization of byte level statistics under intermittent encryption across common file types.<n>We specialize a classical KL divergence upper bound on a tailored mixture model of intermittent encryption, yielding filetype specific detectability ceilings for histogram-based detectors.
  arXiv  Detail & Related papers  (2025-10-16T20:48:22Z)
• Using Modular Arithmetic Optimized Neural Networks To Crack Affine Cryptographic Schemes Efficiently [0.27309692684728615]
  We investigate the cryptanalysis of affine ciphers using a hybrid neural network architecture.<n>Our approach integrates a modular branch that processes raw ciphertext sequences and a statistical branch that leverages letter frequency features.
  arXiv  Detail & Related papers  (2025-07-17T04:54:10Z)
• Provably Secure Public-Key Steganography Based on Admissible Encoding [66.38591467056939]
  The technique of hiding secret messages within seemingly harmless covertext is known as provably secure steganography (PSS)<n>PSS evolves from symmetric key steganography to public-key steganography, functioning without the requirement of a pre-shared key.<n>This paper proposes a more general elliptic curve public key steganography method based on admissible encoding.
  arXiv  Detail & Related papers  (2025-04-28T03:42:25Z)
• Cryptanalysis via Machine Learning Based Information Theoretic Metrics [58.96805474751668]
  We propose two novel applications of machine learning (ML) algorithms to perform cryptanalysis on any cryptosystem.<n>These algorithms can be readily applied in an audit setting to evaluate the robustness of a cryptosystem.<n>We show that our classification model correctly identifies the encryption schemes that are not IND-CPA secure, such as DES, RSA, and AES ECB, with high accuracy.
  arXiv  Detail & Related papers  (2025-01-25T04:53:36Z)
• FoC: Figure out the Cryptographic Functions in Stripped Binaries with LLMs [51.898805184427545]
  We propose a novel framework called FoC to Figure out the Cryptographic functions in stripped binaries.<n>We first build a binary large language model (FoC-BinLLM) to summarize the semantics of cryptographic functions in natural language.<n>We then build a binary code similarity model (FoC-Sim) upon the FoC-BinLLM to create change-sensitive representations and use it to retrieve similar implementations of unknown cryptographic functions in a database.
  arXiv  Detail & Related papers  (2024-03-27T09:45:33Z)
• Leveraging a Randomized Key Matrix to Enhance the Security of Symmetric Substitution Ciphers [0.0]
  An innovative strategy to enhance the security of symmetric substitution ciphers is presented. It is implemented through the implementation of a randomized key matrix suitable for various file formats.
  arXiv  Detail & Related papers  (2023-11-29T21:13:38Z)
• Revocable Cryptography from Learning with Errors [61.470151825577034]
  We build on the no-cloning principle of quantum mechanics and design cryptographic schemes with key-revocation capabilities. We consider schemes where secret keys are represented as quantum states with the guarantee that, once the secret key is successfully revoked from a user, they no longer have the ability to perform the same functionality as before.
  arXiv  Detail & Related papers  (2023-02-28T18:58:11Z)
• Using Topological Data Analysis to classify Encrypted Bits [0.0]
  Persistent homology is applied to generate topological features of a point cloud obtained from sets of encryptions. We see that this machine learning pipeline is able to classify our data successfully where classical models of machine learning fail to perform the task.
  arXiv  Detail & Related papers  (2023-01-18T09:43:00Z)
• Improved Code Summarization via a Graph Neural Network [96.03715569092523]
  In general, source code summarization techniques use the source code as input and outputs a natural language description. We present an approach that uses a graph-based neural architecture that better matches the default structure of the AST to generate these summaries.
  arXiv  Detail & Related papers  (2020-04-06T17:36:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.