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| Main Author: | |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.16669 |
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| _version_ | 1866911603541147648 |
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| author | Kebande, Victor |
| author_facet | Kebande, Victor |
| contents | 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 |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_16669 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Stringology Based Cryptology Kebande, Victor Cryptography and Security 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 |
| title | Stringology Based Cryptology |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2604.16669 |