Sirvi Autor "Kopal, Nils" järgi

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A Typology for Cipher Key Instructions in Early Modern Times
(Tartu University Library, 2024) Megyesi, Beáta; Láng, Benedek; Kopal, Nils; Mikhalev, Vasily; Tudor, Crina; Waldispühl, Michelle; Waldispühl, Michelle; Megyesi, Beáta
We present an empirical study on instructions found in historical cipher keys dating back to early modern times in Europe. The study reveals that instructions in historical cipher keys are prevalent, covering a wide range of themes related to the practical application of ciphers. These include general information about the structure or usage of the cipher key, as well as specific instructions on their application. Being a hitherto neglected genre, these texts provide insight into the practice of cryptographic operations.
Cryptanalysis of Hagelin M-209 Cipher Machine with Artificial Neural Networks: A Known-Plaintext Attack
(Tartu University Library, 2024) Mikhalev, Vasily; Kopal, Nils; Esslinger, Bernhard; Lampesberger, Harald; Hermann, Eckehard; Waldispühl, Michelle; Megyesi, Beáta
This paper introduces a machine learning (ML) approach for cryptanalysis of the ciphermachine Hagelin M-2091. For recovering the part of the secret key, represented by the wheel pins, we use Artificial Neural Networks (ANN) which take as input the pseudo-random displacement values generated by the internal mechanism of the machine. The displacement values can be easily obtained when ciphertext and plaintext are known. In particular, we are using several distinct ANNs, each recovering exactly one pin. Thus, to recover all the 131 pins, we utilize 131 model seach solving a binary classification problem. By experimenting with various ANN architectures and ciphertext lengths, ranging from 52 to 200 characters, we identified an ANN architecture that outperforms others in accuracy. This model, inspired by the architecture by Gohr used for attacking modern ciphers, achieved the following accuracies in recovering the pins of the first wheel of the machine: approximately 71% for 52-characters sequences, 88% for 104-characters, 96% for 200-characters. The first wheel has the largest size and hence represents the most complicated case. For the other wheels, these accuracies are slightly higher. To the best of our knowledge, this is the first time when ANNs are used in a key-recovery attack against such machines.
Decipherment of a German encrypted letter sent from Sigismund Heusner von Wandersleben to Axel Oxenstierna in 1637
(Tartu University Library, 2024) Waldispühl, Michelle; Kopal, Nils; Waldispühl, Michelle; Megyesi, Beáta
We present our work on an encrypted letter from the Thirty Years’ War written by the ally of the Swedish Empire, Sigismund Heusner von Wandersleben in 1637 and sent from Kassel to the Swedish High Lord Chancellor Axel Oxenstierna. We describe our analysis of the ciphertext including information on the cipher type, the process of cryptanalysis and challenges for the decipherment. We include the edition of the letter in the current state of decipherment and summarize its content.
Decipherment of an Encrypted Letter from 1724 Found in UCL Special Collections’ Brougham Archive
(Tartu University Library, 2024) Kopal, Nils; Makin, Katy; Waldispühl, Michelle; Megyesi, Beáta
This paper shows the decipherment of a 1724 encrypted letter, discovered recently in the Brougham Archive at University College London (UCL) Special Collections. The letter’s content hints at political intrigue and possibly relates to the Jacobite movement during George I’s reign in Great Britain. However, as all individuals mentioned in the letter are referred to bycode names, except for Madame de Prie, their true identities remain unknown to the authors. Therefore, any connection to the Jacobites remains speculative. The paper covers the cipher’s security, historical context, and unresolved inquiries surrounding the letter.
Decipherment of Historical Manuscripts with Unknown or Rare Writings: The DESCRYPT Project
(Tartu University Library, 2025) Megyesi, Beáta; Fornés, Alicia; Héder, Mihály; Heil, Raphaela; Kopal, Nils; Láng, Benedek; Rattenborg, Rune; Waldispühl, Michelle; Antal, Eugen; Marák, Pavol
We present a newly funded research program, DESCRYPT, aimed at deciphering and analyzing historical texts with rare or unknown scripts. The project leverages advancements in computational linguistics, artificial intelligence (AI), and image processing, alongside traditional philological methods, to develop innovative tools for transcription, recognition, and interpretation of historical writings with rare/unknown scripts, including ciphertexts. By integrating interdisciplinary expertise, DESCRYPT addresses the challenges posed by complex and undeciphered texts, preserving and unlocking the secrets of our shared cultural heritage.
Enhancing Classical Cipher Type Detection: Prompt Engineering with Common LLMs versus Usage of Custom AI Models
(Tartu University Library, 2025) Bastian, Maik; Esslinger, Bernhard; Hermann, Eckehard; Kopal, Nils; Lampesberger, Harald; Antal, Eugen; Marák, Pavol
In the field of cryptography, identifying the type of cipher used in an encrypted message is crucial to effective cryptanalysis. Thus far, from a machine learning perspective, this classification problem has been tackled using specifically designed models, such as the Neural Cipher Identifier (NCID), which require data generation and model training capabilities. The recent advent of Large Language Models (LLMs) raises the following question: Can this classification problem be approached more effectively through prompt engineering? This paper explores various generic strategies for prompt engineering, such as chain-of-thought and in-context learning, by evaluating thousands of generated prompts for classical ciphers using open-source LLMs (on an Nvidia DGX system) and ChatGPT (via a browser interface and API). The classification accuracies achieved through these prompting techniques are compared with those obtained by NCID. Although our findings indicate that NCID still significantly outperforms the use of LLMs for cipher-type detection, the latter offers a more accessible approach to cryptography tasks. Both methods can benefit from domain-specific knowledge in cryptanalysis, highlighting the importance of expert input in improving initial classifications and handling complex cipher types.
Send someone to finish Fredenburgh’s works. A Dutch ciphertext (1689) from Suriname
(Tartu University Library, 2024) Dinnissen, Jörgen; Kopal, Nils; Waldispühl, Michelle; Megyesi, Beáta
A ciphertext without its corresponding key was found in the archives from the Dutch colony Suriname, in the National Archives at The Hague. We were able to decrypt it through cryptanalysis and with the use of CrypTool2. The revealed plaintext contains a letter with military sensitive information and the name of Fredenburgh, who served as Governor ad interim from 1688 to 1689. It was sent in May 1689 by Governor Van Scharphuijsen to his directors in Amsterdam. Since 1689, the Society of Suriname (SvS) used ciphers for its militarily sensitive information. Ciphertext U3 was sent during the Nine Years’ War (1688-1697) when the Dutch were at war with the French. The letter was encrypted as a precaution against possible interception by the (French) enemy.
Supporting Historical Cryptology: The Decrypt Pipeline
(Tartu University Library, 2024) Héder, Mihály; Fornés, Alicia; Kopal, Nils; Szigeti, Ferenc; Megyesi, Beáta; Waldispühl, Michelle; Megyesi, Beáta
We present a set of resources and tools to support research and development in the field of historical cryptology. The tools aim to support transcription and decipherment of ciphertexts, developed to work together in a pipeline. It encompasses cataloging these documents into the Decode database, which houses ciphers dating from the 14th century to 1965, transcription using both manual and AI-assisted methods, cryptanalysis, and subsequent historical and linguistic analysis to contextualize decrypted content. The project encounters challenges with the accuracy of automated transcription technologies and the necessity for significant user involvement in the transcription and analysis processes. These insights highlight the critical balance between technological innovation and the indispensable input of domain expertise in advancing the field of historical cryptology.