pith. sign in

arxiv: 2604.08862 · v1 · submitted 2026-04-10 · 💻 cs.CR

Stringology-Based Cryptanalysis for EChaCha20 Stream Cipher

Victor Kebande This is my paper

Pith reviewed 2026-05-10 18:04 UTC · model grok-4.3

classification 💻 cs.CR
keywords EChaCha20stream ciphercryptanalysisKnuth-Morris-PrattBoyer-Moorepseudorandomnessrotational attacksARX ciphers
0
0 comments X

The pith

EChaCha20 keystreams exhibit strong pseudorandomness at 16- and 32-bit levels with no significant rotational collisions under string pattern analysis.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper applies adapted versions of the Knuth-Morris-Pratt and Boyer-Moore algorithms to scan one million EChaCha20 keystream samples for m-bit patterns and rotational biases at the 32-bit word level. The central effort tests whether the cipher's expanded 6x6 state matrix and modified quarter-round function create detectable structural weaknesses that conventional statistical tests might miss. Results indicate uniform pattern distributions at higher bit widths, rapid diffusion after two rounds, and absence of meaningful collisions, which would support the cipher's resistance to rotational-differential attacks if confirmed. A sympathetic reader would care because such findings help validate design changes in ARX stream ciphers before deployment in security-critical systems. The work frames stringology as a practical complement to existing evaluation methods for these constructions.

Core claim

Leveraging optimized KMP and BM adaptations for 32-bit word-level pattern frequency analysis on large-scale datasets shows that EChaCha20 maintains strong pseudorandomness at 16-bit and 32-bit levels, with only minor irregularities in the 8-bit domain. Differential testing reveals an avalanche effect after two QR-F rounds and no statistically significant rotational collisions within the evaluated bounds, matching expected ARX diffusion behavior beyond three rounds. The paper concludes that these outcomes affirm the cipher's security properties and position stringology-based cryptanalysis as a complementary tool for ARX cipher assessment.

What carries the argument

Adapted Knuth-Morris-Pratt (KMP) and Boyer-Moore (BM) algorithms for 32-bit word-level m-bit pattern frequency analysis to detect rotational biases or partial collisions in keystreams.

If this is right

  • EChaCha20 resists rotational-differential attacks within the tested sample bounds and bit widths.
  • The 6x6 state matrix and enhanced QR-F deliver rapid diffusion without introducing detectable keystream weaknesses.
  • Stringology methods can serve as a routine complement to statistical tests when evaluating ARX stream ciphers.
  • Minor 8-bit irregularities do not propagate to compromise higher-bit pseudorandomness in the examined data.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar stringology scans on the original ChaCha20 could quantify whether the 6x6 expansion improves or merely preserves diffusion properties.
  • Extending the tests to multi-gigabyte keystream volumes or varying pattern lengths might expose rare events missed by the current sample size.
  • The approach could be automated into open cryptanalysis libraries for ongoing monitoring of ARX variants during design iterations.

Load-bearing premise

The KMP and BM adaptations for word-level analysis are sensitive enough to detect any real subtle patterns, biases, or collisions if they exist in EChaCha20.

What would settle it

A new set of one million keystream samples showing statistically significant non-uniform m-bit pattern distributions or rotational collisions at the 32-bit level would falsify the central claim.

Figures

Figures reproduced from arXiv: 2604.08862 by Victor Kebande.

Figure 1
Figure 1. Figure 1: The evolution from ChaCha20 (left) to EChaCha20 (right). The original 4×4 state (left) uses rotations of 16, 12, 8, and 7 bits. EChaCha20 expands to 6×6 (right) while adding 4-bit (purple) and 2-bit (cyan) rotations to its QR-F. 2.1 ChaCha20 The ChaCha20 cipher was introduced by Bernstein in 2008 [10]. Since then, it has revolutionized the design of the stream cipher design due to its robust Add-Rotate-XOR… view at source ↗
Figure 2
Figure 2. Figure 2: Initial state matrix of ECHACHA State =   m0 m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 m11 m12 m13 m14 m15 m16 m17 m18 m19 m20 m21 m22 m23 m24 m25 m26 m27 m28 m29 m30 m31 m32 m33 m34 m35   (2) where each mi represents a 32-bit word, totaling 1,152 bits of internal state (vs. ChaCha20’s 512 bits). 2.2.2 Enhanced Quarter-Round Function Equation 3 shows the QR-F, which incorporates two additional rotation … view at source ↗
Figure 3
Figure 3. Figure 3: Threat Model attack goals based on KPE and CPE [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Attacker workflow in the proposed threat model. Red arrows indicate the attack path from inputs to [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Methodology that shows the progression from data preparation through analysis phases to experimental [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: The complete workflow for Pattern Frequency Analysis experiment. Phase 1 generates 1 million keystream [PITH_FULL_IMAGE:figures/full_fig_p018_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Top 10 most frequently occurring m-bit patterns in EChaCha20 keystreams for m ∈ {8, 16, 32}. Each subplot shows the distribution of the most common patterns detected across 10,000 blocks of 1,152-bit keystreams. The x-axis denotes hashed identifiers (in decimal) of observed patterns, while the y-axis represents the frequency of occurrence. The uniformity at 16-bit and 32-bit levels demonstrates strong pseu… view at source ↗
Figure 8
Figure 8. Figure 8: Top 10 most frequently occurring m-bit patterns in EChaCha20 keystreams for m ∈ {8, 16, 32}. Each subplot shows the distribution of patterns detected across a larger sample of 10 million blocks. The consistent distribution across bit-lengths confirms the cipher’s robustness against pattern frequency attacks, with minor deviations only appearing in the 8-bit analysis. 7.1.3 32-bit Pattern Frequency In 32-bi… view at source ↗
Figure 9
Figure 9. Figure 9: Propagation of rotational differences across [PITH_FULL_IMAGE:figures/full_fig_p021_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Impact of the rotation constants on differential diffusion. Both collision probability and average flipped bits [PITH_FULL_IMAGE:figures/full_fig_p021_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Avalanche effect of EChaCha20 after 2 QR-F rounds. Bit flip probability is measured per bit position across four state words, showing uniform diffusion close to the ideal 0.5 threshold [PITH_FULL_IMAGE:figures/full_fig_p022_11.png] view at source ↗
read the original abstract

Stringology-Based Cryptanalysis (SBC) offers a suitable and a structurally aligned approach for uncovering structural patterns in stream ciphers that traditional statistical tests may often fail to detect. Despite \texttt{EChaCha20}'s design enhancements, no systematic investigation has been performed to determine whether its expanded 6$\times$6 state matrix and modified Quarter-Round Function (\texttt{QR-F}) introduce subtle keystream patterns, rotational biases, or partial collisions that could serve as statistical distinguishers. As such, addressing this gap is critical to ensure that the cipher's modifications do not unintentionally reduce its security margin. Therefore, this paper leverages Knuth-Morris-Pratt (\texttt{KMP}) and Boyer-Moore (\texttt{BM}) algorithms to analyze \texttt{EChaCha20}, which is a variant of ChaCha20 that features an expanded 6$\times$6 state matrix and an enhanced \texttt{QR-F}. The author has developed and optimized adaptations of the \texttt{KMP} and \texttt{BM} algorithms for 32-bit word level pattern analysis and employed them to investigate $m$-bit pattern frequency distributions to assess the \texttt{EChaCha20}'s resistance of rotational-differential attacks. Our experimental results on large-scale one million keystream datasets have confirmed that \texttt{EChaCha20} is able to maintain strong pseudorandomness at 16-bit and 32-bit levels with minor irregularities observed in the 8-bit domain. In addition to these, the differential tests have indicated a rapid diffusion, exhibiting an avalanche effect after two \texttt{QR-F} rounds and no statistically significant rotational collisions were observed within the evaluated bounds, consistent with expected ARX diffusion behavior beyond 3 rounds. This work puts forward SBC as a complementary tool for ARX cipher evaluation and provide new thoughts on the security properties of \texttt{EChaCha20}.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper proposes Stringology-Based Cryptanalysis (SBC) as a method to detect subtle patterns in the EChaCha20 stream cipher (a 6x6-state variant of ChaCha20 with modified QR-F) by adapting the KMP and BM string-matching algorithms for 32-bit word-level m-bit pattern frequency analysis. Experiments on one million keystreams are reported to confirm strong pseudorandomness at 16-bit and 32-bit levels (with minor irregularities at 8 bits), rapid diffusion with avalanche effect after two QR-F rounds, and no statistically significant rotational collisions.

Significance. If the adapted algorithms are shown to be sensitive to known ARX biases and the statistical methodology is fully documented, the work could provide a useful complementary tool to traditional randomness tests for ARX cipher evaluation. The scale of the one-million-keystream experiments is a strength, but the current lack of validation and detail limits the significance of the security claims.

major comments (3)
  1. [Abstract] Abstract: The central claim that EChaCha20 exhibits 'strong pseudorandomness' and 'no statistically significant rotational collisions' rests on experimental observations, yet no details are supplied on keystream lengths, sampling procedure (random keys vs. fixed-key nonces), exact definitions of 'minor irregularities,' statistical tests applied, error bars, or exclusion criteria. This directly undermines the ability to evaluate the evidence for the pseudorandomness and diffusion claims.
  2. [Abstract] Abstract (experimental results): No baseline experiments are described on reduced-round ChaCha20 or other ARX designs known to exhibit biases or collisions. Without such controls, it is impossible to confirm that the adapted KMP and BM algorithms are sensitive enough to detect weaknesses when present, which is load-bearing for interpreting the negative results (absence of collisions) as support for security.
  3. [Abstract] Abstract (methods description): The adaptations of KMP and BM for 32-bit word-level pattern analysis, including how m-bit pattern frequencies and rotational collisions are defined, computed, and tested for significance, receive no technical description. This prevents assessment of whether the stringology approach offers any advantage over standard statistical batteries for ARX analysis.
minor comments (2)
  1. [Abstract] Abstract: Minor grammatical issues include 'provide new thoughts' (should be 'provides') and 'resistance of rotational-differential attacks' (should be 'resistance to').
  2. [Abstract] Abstract: The abbreviation 'QR-F' is introduced without expansion on first use, although 'Quarter-Round Function' appears later in the same paragraph.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive and detailed comments, which highlight important areas for improving the clarity and rigor of our work. We will make substantial revisions to address the concerns about experimental documentation, validation baselines, and methodological transparency. Our point-by-point responses follow.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The central claim that EChaCha20 exhibits 'strong pseudorandomness' and 'no statistically significant rotational collisions' rests on experimental observations, yet no details are supplied on keystream lengths, sampling procedure (random keys vs. fixed-key nonces), exact definitions of 'minor irregularities,' statistical tests applied, error bars, or exclusion criteria. This directly undermines the ability to evaluate the evidence for the pseudorandomness and diffusion claims.

    Authors: We agree that the abstract requires more precise experimental details to support the claims. In the revised manuscript we will expand the abstract and add a dedicated Methods subsection specifying: keystream length of 2^20 bytes per sample; generation using uniformly random 256-bit keys and 96-bit nonces; definition of 'minor irregularities' as 8-bit frequency deviations exceeding two standard deviations from uniformity in under 5% of streams; application of chi-square goodness-of-fit tests with p-value reporting; and error bars derived from the one-million-sample ensemble. Exclusion criteria (streams failing basic length or format checks) will also be stated. revision: yes

  2. Referee: [Abstract] Abstract (experimental results): No baseline experiments are described on reduced-round ChaCha20 or other ARX designs known to exhibit biases or collisions. Without such controls, it is impossible to confirm that the adapted KMP and BM algorithms are sensitive enough to detect weaknesses when present, which is load-bearing for interpreting the negative results (absence of collisions) as support for security.

    Authors: The referee correctly notes the absence of positive controls. We will add a new subsection in the revised paper presenting baseline results: the same KMP/BM pipeline applied to 4-round and 8-round ChaCha20 (known to retain detectable rotational biases) and to a deliberately weakened ARX variant. These controls will show that the stringology method identifies the expected pattern deviations and collisions, thereby confirming its sensitivity and strengthening the interpretation of the EChaCha20 negative results. revision: yes

  3. Referee: [Abstract] Abstract (methods description): The adaptations of KMP and BM for 32-bit word-level pattern analysis, including how m-bit pattern frequencies and rotational collisions are defined, computed, and tested for significance, receive no technical description. This prevents assessment of whether the stringology approach offers any advantage over standard statistical batteries for ARX analysis.

    Authors: While the full manuscript contains a technical description of the adaptations in Section 4, we acknowledge that the abstract and early sections are insufficiently explicit. In the revision we will insert a concise methods summary into the abstract and ensure Section 3 provides explicit definitions: m-bit patterns as contiguous substrings extracted from the 32-bit word stream; frequency counting via optimized KMP/BM automata for linear-time matching; and significance testing via chi-square statistics supplemented by Monte Carlo estimation of rotational-collision probabilities under the null hypothesis of uniformity. revision: yes

Circularity Check

0 steps flagged

No circularity: claims rest on direct empirical observations

full rationale

The paper reports experimental results obtained by running adapted KMP and BM string-matching algorithms on one million generated keystreams. The conclusions (strong pseudorandomness at 16/32-bit levels, avalanche after two QR-F rounds, absence of significant rotational collisions) are stated as direct observations from those runs. No equations, fitted parameters presented as predictions, self-definitional loops, or load-bearing self-citations appear in the supplied text. The method is an empirical test whose outcome is not forced by construction from its own inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the domain assumption that string-matching algorithms can serve as effective distinguishers for ARX cipher weaknesses; no free parameters or invented entities are introduced in the abstract.

axioms (1)
  • domain assumption Adaptations of KMP and BM algorithms can be used for m-bit pattern frequency analysis in 32-bit word keystreams to detect rotational-differential biases.
    Invoked when the paper states it developed and optimized these adaptations for the EChaCha20 analysis.

pith-pipeline@v0.9.0 · 5641 in / 1444 out tokens · 57337 ms · 2026-05-10T18:04:04.654342+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Structural Analysis of Cryptographic Sequences using Stringology-Based Fingerprinting

    cs.CR 2026-05 unverdicted novelty 5.0

    Introduces SBF framework that extracts structural string patterns from cryptographic sequences to produce measurable fingerprints distinguishing different generators.

  2. Stringology Based Cryptology

    cs.CR 2026-04 unverdicted novelty 5.0

    Stringology-Based Cryptology applies substring recurrence and pattern-frequency metrics to cryptographic sequences to reveal structural properties beyond statistical randomness tests.

  3. Neural Stringology Based Cryptanalysis of EChaCha20

    cs.CR 2026-04 unverdicted novelty 5.0

    A new framework using stringology features and neural learning detects distinguishable structural patterns in EChaCha20 keystreams under reduced-round conditions.

Reference graph

Works this paper leans on

55 extracted references · 55 canonical work pages · cited by 3 Pith papers

  1. [1]

    Hidden stream ciphers and tmto attacks on tls 1.3, dtls 1.3, quic, and signal

    John Preuß Mattsson. Hidden stream ciphers and tmto attacks on tls 1.3, dtls 1.3, quic, and signal. InInternational Conference on Cryptology and Network Security, pages 251–267. Springer, 2023

    work page 2023

  2. [2]

    A survey on stream ciphers for constrained environments

    Sameeh A Jassim and Alaa K Farhan. A survey on stream ciphers for constrained environments. In2021 1st Babylon International Conference on Information Technology and Science (BICITS), pages 228–233. IEEE, 2021

    work page 2021

  3. [3]

    Error analysis of nist sp 800-22 test suite.IEEE Transactions on Information Forensics and Security, 18:3745–3759, 2023

    Dongyu Chen, Hua Chen, Limin Fan, and Kai Luo. Error analysis of nist sp 800-22 test suite.IEEE Transactions on Information Forensics and Security, 18:3745–3759, 2023

    work page 2023

  4. [4]

    An overview on cryptanalysis of arx ciphers.DE CIFRIS KOINE, page 10, 2024

    Stefano Barbero. An overview on cryptanalysis of arx ciphers.DE CIFRIS KOINE, page 10, 2024

    work page 2024

  5. [5]

    Testu01 and practrand: Tools for a randomness evaluation for famous multimedia ciphers.Multimedia Tools and Applications, 79(33):24075–24088, 2020

    Lama Sleem and Raphaël Couturier. Testu01 and practrand: Tools for a randomness evaluation for famous multimedia ciphers.Multimedia Tools and Applications, 79(33):24075–24088, 2020

    work page 2020

  6. [6]

    Extended-chacha20 stream cipher with enhanced quarter round function.IEEE Access, 11:114220–114237, 2023

    Victor R Kebande. Extended-chacha20 stream cipher with enhanced quarter round function.IEEE Access, 11:114220–114237, 2023

    work page 2023

  7. [7]

    Performance and implementation comparison of knuth-morris-pratt and boyer-moore string search algorithms

    Taj Saleh, Fatma Corut Ergin, Malek Malkawi, and Reda Alhajj. Performance and implementation comparison of knuth-morris-pratt and boyer-moore string search algorithms. In2025 2nd International Conference on Advanced Innovations in Smart Cities (ICAISC), pages 1–7. IEEE, 2025

    work page 2025

  8. [8]

    Cryptanalysis of arx-based white-box implementations

    Alex Biryukov, Baptiste Lambin, and Aleksei Udovenko. Cryptanalysis of arx-based white-box implementations. IACR Transactions on Cryptographic Hardware and Embedded Systems, 2023(3):97–135, 2023

    work page 2023

  9. [9]

    Further analysis of the statistical independence of the nist sp 800-22 randomness tests.Applied Mathematics and Computation, 459:128222, 2023

    Elena Almaraz Luengo, Bittor Alaña Olivares, Luis Javier García Villalba, and Julio Hernandez-Castro. Further analysis of the statistical independence of the nist sp 800-22 randomness tests.Applied Mathematics and Computation, 459:128222, 2023

    work page 2023

  10. [10]

    Chacha, a variant of salsa20

    Daniel J Bernstein et al. Chacha, a variant of salsa20. InWorkshop record of SASC, volume 8, pages 3–5. Lausanne, Switzerland, 2008

    work page 2008

  11. [11]

    Design, diffusion, and cryptanalysis of symmetric primitive.repositorio.unb.br, 2023

    Murilo Coutinho Silva. Design, diffusion, and cryptanalysis of symmetric primitive.repositorio.unb.br, 2023

    work page 2023

  12. [12]

    Higher-order differential-linear cryptanalysis of chacha stream cipher

    Nasratullah Ghafoori and Atsuko Miyaji. Higher-order differential-linear cryptanalysis of chacha stream cipher. IEEE Access, 12:13386–13399, 2024

    work page 2024

  13. [13]

    PhD thesis, PhD thesis, 2024

    Nasratullah Ghafoori.A Study on Differential Cryptanalysis of Salsa. PhD thesis, PhD thesis, 2024

    work page 2024

  14. [14]

    Exact string matching algorithms: survey, issues, and future research directions.IEEE access, 7:69614–69637, 2019

    Saqib Iqbal Hakak, Amirrudin Kamsin, Palaiahnakote Shivakumara, Gulshan Amin Gilkar, Wazir Zada Khan, and Muhammad Imran. Exact string matching algorithms: survey, issues, and future research directions.IEEE access, 7:69614–69637, 2019

    work page 2019

  15. [15]

    Pattern matching in strings

    Alfred V Aho. Pattern matching in strings. InFormal Language Theory, pages 325–347. Elsevier, 1980

    work page 1980

  16. [16]

    Correctness-by-construction in stringology

    Bruce W Watson. Correctness-by-construction in stringology. InStringology, pages 1–2, 2012

    work page 2012

  17. [17]

    Adapting the knuth–morris–pratt algorithm for pattern matching in huffman encoded texts.Information processing & management, 42(2):429–439, 2006

    Dana Shapira and Ajay Daptardar. Adapting the knuth–morris–pratt algorithm for pattern matching in huffman encoded texts.Information processing & management, 42(2):429–439, 2006

    work page 2006

  18. [18]

    On compile time knuth-morris-pratt precomputation

    Justin Kourie, LGWA Cleophas, and BW Watson. On compile time knuth-morris-pratt precomputation. In Proceedings of the Prague Stringology Conference 2011 (PSC’11, Prague, Czech Republic, August 29-31, 2011), pages 15–29. Czech Technical University in Prague, 2011

    work page 2011

  19. [19]

    World Scientific, 2002

    Maxime Crochemore and Wojciech Rytter.Jewels of stringology: text algorithms. World Scientific, 2002

    work page 2002

  20. [20]

    Optimal packed string matching

    Oren Ben-Kiki, Philip Bille, Dany Breslauer, Leszek Gasieniec, Roberto Grossi, and Oren Weimann. Optimal packed string matching. InIARCS annual conference on foundations of software technology and theoretical computer science (FSTTCS 2011), pages 423–432. Schloss Dagstuhl–Leibniz-Zentrum für Informatik, 2011

    work page 2011

  21. [21]

    A hybrid length- based pattern matching algorithm for text searching.International Journal of Advanced Computer Science & Applications, 16(4), 2025

    Victor Cornejo-Aparicio, Cesar Cuarite-Silva, Antoni Benavente-Mayta, and Karim Guevara. A hybrid length- based pattern matching algorithm for text searching.International Journal of Advanced Computer Science & Applications, 16(4), 2025

    work page 2025

  22. [22]

    A boyer–moore-style algorithm for regular expression pattern matching

    Bruce W Watson and Richard E Watson. A boyer–moore-style algorithm for regular expression pattern matching. Science of Computer Programming, 48(2-3):99–117, 2003. 27 APREPRINT- APRIL13, 2026

    work page 2003

  23. [23]

    John wiley & sons, 2014

    Michael T Goodrich, Roberto Tamassia, and Michael H Goldwasser.Data structures and algorithms in Java. John wiley & sons, 2014

    work page 2014

  24. [24]

    On boyer-moore preprocessing.Department of Computer Sciences, University of Tampere, Series of Publications, D-NET Publications, D-2004-1, 2004

    Heikki Hyyrö. On boyer-moore preprocessing.Department of Computer Sciences, University of Tampere, Series of Publications, D-NET Publications, D-2004-1, 2004

    work page 2004

  25. [25]

    Fast detection algorithm for equal length frame signals based on pattern matching

    Zhongyong Wang, Shufeng Zhang, Hong Sun, Kexian Gong, Honghua Liu, and Wei Wang. Fast detection algorithm for equal length frame signals based on pattern matching. InProceedings of the 2nd International Conference on Signal Processing, Computer Networks and Communications, pages 402–407, 2023

    work page 2023

  26. [26]

    Authenticated key exchange secure against dictionary attacks

    Mihir Bellare, David Pointcheval, and Phillip Rogaway. Authenticated key exchange secure against dictionary attacks. InInternational conference on the theory and applications of cryptographic techniques, pages 139–155. Springer, 2000

    work page 2000

  27. [27]

    Decoding substitution ciphers by means of word matching with application to ocr.IEEE Transactions on Pattern Analysis and Machine Intelligence, 5:710–715, 1987

    George Nagy, Sharad Seth, and Kent Einspahr. Decoding substitution ciphers by means of word matching with application to ocr.IEEE Transactions on Pattern Analysis and Machine Intelligence, 5:710–715, 1987

    work page 1987

  28. [28]

    Rotational cryptanalysis of arx

    Dmitry Khovratovich and Ivica Nikoli ´c. Rotational cryptanalysis of arx. InInternational Workshop on Fast Software Encryption, pages 333–346. Springer, 2010

    work page 2010

  29. [29]

    Rotational cryptanalysis on chacha stream cipher

    Stefano Barbero, Danilo Bazzanella, and Emanuele Bellini. Rotational cryptanalysis on chacha stream cipher. Symmetry, 14(6):1087, 2022

    work page 2022

  30. [30]

    PhD thesis, King’s College London, 2021

    Oluwole Ajala.Efficient String Algorithms for Data Security and Privacy. PhD thesis, King’s College London, 2021

    work page 2021

  31. [31]

    PhD thesis, University of Haifa (Israel), 2024

    Samah Idrees Ghazawi.Algorithms and Combinatorics in 1D and 2D Strings. PhD thesis, University of Haifa (Israel), 2024

    work page 2024

  32. [32]

    Performance analysis of current lightweight stream ciphers for constrained environments.S ¯adhan¯a, 45(1):256, 2020

    Subhrajyoti Deb and Bubu Bhuyan. Performance analysis of current lightweight stream ciphers for constrained environments.S ¯adhan¯a, 45(1):256, 2020

    work page 2020

  33. [33]

    Colour image encryption using an improved version of stream cipher and chaos.International Journal of Ad Hoc and Ubiquitous Computing, 41(2):118–133, 2022

    Subhrajyoti Deb, Bubu Bhuyan, Nirmalya Kar, and K Sudheer Reddy. Colour image encryption using an improved version of stream cipher and chaos.International Journal of Ad Hoc and Ubiquitous Computing, 41(2):118–133, 2022

    work page 2022

  34. [34]

    A quantum circuit for the cyclic string matching problem

    Arianna Pavone and Caterina Viola. A quantum circuit for the cyclic string matching problem. InProceedings of the Prague Stringology Conference, 2024

    work page 2024

  35. [35]

    Efficient and secure pattern matching with wildcards using lightweight cryptography.Computers & Security, 77:666–674, 2018

    Javad Darivandpour and Mikhail J Atallah. Efficient and secure pattern matching with wildcards using lightweight cryptography.Computers & Security, 77:666–674, 2018

    work page 2018

  36. [36]

    Bdd-based cryptanalysis of stream cipher: a practical approach.IET Information Security, 11(3):159–167, 2017

    Harish Kumar Sahu, Indivar Gupta, N Rajesh Pillai, and Rajendra Kumar Sharma. Bdd-based cryptanalysis of stream cipher: a practical approach.IET Information Security, 11(3):159–167, 2017

    work page 2017

  37. [37]

    A nonlinear stream cipher for encryption of test patterns in streaming scan networks.IEEE Transactions on Circuits and Systems I: Regular Papers, 2024

    Janusz Rajski, Maciej Trawka, Jerzy Tyszer, and Bartosz Włodarczak. A nonlinear stream cipher for encryption of test patterns in streaming scan networks.IEEE Transactions on Circuits and Systems I: Regular Papers, 2024

    work page 2024

  38. [38]

    Test data encryption with a new stream cipher

    Janusz Rajski, Maciej Trawka, Jerzy Tyszer, and Bartosz Włodarczak. Test data encryption with a new stream cipher. In2024 IEEE International Test Conference (ITC), pages 313–322. IEEE, 2024

    work page 2024

  39. [39]

    Randomness evaluation of stream cipher for secure mobile communication

    Musheer Ahmad et al. Randomness evaluation of stream cipher for secure mobile communication. In2010 First International Conference On Parallel, Distributed and Grid Computing (PDGC 2010), pages 180–183. IEEE, 2010

    work page 2010

  40. [40]

    rfc7539: Chacha20 and poly1305 for ietf protocols, 2021

    Adam Langley and Yael Nir. rfc7539: Chacha20 and poly1305 for ietf protocols, 2021

    work page 2021

  41. [41]

    Ind-cpa-d of relaxed functional bootstrapping: A new attack, a general fix, and a stronger model

    Zeyu Liu, Yunhao Wang, and Ben Fisch. Ind-cpa-d of relaxed functional bootstrapping: A new attack, a general fix, and a stronger model. InProceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security, pages 2907–2921, 2025

    work page 2025

  42. [42]

    The bonferroni adjustment.Statistics, 12(1):23–27, 2008

    James Dean Brown. The bonferroni adjustment.Statistics, 12(1):23–27, 2008

    work page 2008

  43. [43]

    The salsa20 family of stream ciphers

    Daniel J Bernstein. The salsa20 family of stream ciphers. InNew stream cipher designs, pages 84–97. Springer, 2008

    work page 2008

  44. [44]

    Xchacha: extended-nonce chacha and aead xchacha20 poly1305.Internet Engineering Task Force, Internet-Draft draft-irtf-cfrg-xchacha-03, 2020

    Scott Arciszewski. Xchacha: extended-nonce chacha and aead xchacha20 poly1305.Internet Engineering Task Force, Internet-Draft draft-irtf-cfrg-xchacha-03, 2020

    work page 2020

  45. [45]

    Memory-based architecture for multicharacter aho–corasick string matching.IEEE transactions on very large scale integration (VLSI) systems, 26(1):143–154, 2017

    Xing Wang and Derek Pao. Memory-based architecture for multicharacter aho–corasick string matching.IEEE transactions on very large scale integration (VLSI) systems, 26(1):143–154, 2017

    work page 2017

  46. [46]

    An efficient multicharacter transition string-matching engine based on the aho-corasick algorithm.ACM Transactions on Architecture and Code Optimization (TACO), 10(4):1–22, 2013

    Chien-Chi Chen and Sheng-De Wang. An efficient multicharacter transition string-matching engine based on the aho-corasick algorithm.ACM Transactions on Architecture and Code Optimization (TACO), 10(4):1–22, 2013. 28 APREPRINT- APRIL13, 2026

    work page 2013

  47. [47]

    A fast plain copy-move detection algorithm based on structural pattern and 2d rabin-karp rolling hash

    Kuznetsov Andrey Vladimirovich and Myasnikov Vladislav Valerievich. A fast plain copy-move detection algorithm based on structural pattern and 2d rabin-karp rolling hash. InInternational Conference Image Analysis and Recognition, pages 461–468. Springer, 2014

    work page 2014

  48. [48]

    S-box design based on logistic skewed chaotic map and modified rabin-karp algorithm: applications to multimedia security.Physica Scripta, 99(5):055236, 2024

    Adil Waheed and Fazli Subhan. S-box design based on logistic skewed chaotic map and modified rabin-karp algorithm: applications to multimedia security.Physica Scripta, 99(5):055236, 2024

    work page 2024

  49. [49]

    Ciphermatch: Accelerating homomorphic encryption- based string matching via memory-efficient data packing and in-flash processing

    Mayank Kabra, Rakesh Nadig, Harshita Gupta, Rahul Bera, Manos Frouzakis, Vamanan Arulchelvan, Yu Liang, Haiyu Mao, Mohammad Sadrosadati, and Onur Mutlu. Ciphermatch: Accelerating homomorphic encryption- based string matching via memory-efficient data packing and in-flash processing. InProceedings of the 30th ACM International Conference on Architectural S...

    work page 2025

  50. [50]

    Full-text and keyword indexes for string searching.arXiv preprint arXiv:1508.06610, 2015

    Aleksander Cisłak. Full-text and keyword indexes for string searching.arXiv preprint arXiv:1508.06610, 2015

    work page arXiv 2015

  51. [51]

    Recommendations on statistical randomness test batteries for cryptographic purposes.ACM Computing Surveys (CSUR), 54(4):1–34, 2021

    Elena Almaraz Luengo and Luis Javier García Villalba. Recommendations on statistical randomness test batteries for cryptographic purposes.ACM Computing Surveys (CSUR), 54(4):1–34, 2021

    work page 2021

  52. [52]

    Statistical testing of cryptographic randomness

    Haydar Demirhan and Nihan Bitirim. Statistical testing of cryptographic randomness. ˙Istatistikçiler Dergisi: ˙Istatistik ve Aktüerya, 9(1):1–11, 2016

    work page 2016

  53. [53]

    The error linear complexity spectrum as a cryptographic criterion of boolean functions.IEEE Transactions on Information Theory, 65(12):8345–8356, 2019

    Konstantinos Limniotis and Nicholas Kolokotronis. The error linear complexity spectrum as a cryptographic criterion of boolean functions.IEEE Transactions on Information Theory, 65(12):8345–8356, 2019

    work page 2019

  54. [54]

    Asmita Poojari, HR Nagesh, et al. Fpga implementation of random number generator using lfsr and scrambling algorithm for lightweight cryptography.International Journal of Applied Science and Engineering, 18(6):1–9, 2021

    work page 2021

  55. [55]

    Bae: Anomaly detection algorithm based on clustering and autoencoder.Mathematics, 11(15):3398, 2023

    Dongqi Wang, Mingshuo Nie, and Dongming Chen. Bae: Anomaly detection algorithm based on clustering and autoencoder.Mathematics, 11(15):3398, 2023. 29

    work page 2023