Can a Tabula Recta provide security in the XXI century?

• URL: http://arxiv.org/abs/2312.02869v1
• Date: Tue, 5 Dec 2023 16:36:27 GMT
• Title: Can a Tabula Recta provide security in the XXI century?
• Authors: Francisco Ruiz
• Abstract summary: I discuss how some human-computable algorithms can indeed afford sufficient security in this situation. Three kinds of algorithms are discussed: those that concentrate entropy from shared text sources, stream ciphers based on arithmetic of non-binary spaces, and hash-like algorithms that may be used to generate a password from a challenge text.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: In the not so unlikely scenario of total compromise of computers accessible to a group of users, they might be tempted to resort to human-computable paper-and-pencil cryptographic methods aided by a classic Tabula Recta, which helps to perform addition and subtraction directly with letters. But do these classic algorithms, or some new ones using the same simple tools, have any chance against computer-aided cryptanalysis? In this paper I discuss how some human-computable algorithms can indeed afford sufficient security in this situation, drawing conclusions from computer-based statistical analysis. Three kinds of algorithms are discussed: those that concentrate entropy from shared text sources, stream ciphers based on arithmetic of non-binary spaces, and hash-like algorithms that may be used to generate a password from a challenge text.

Related papers

• Post-Quantum Security: Origin, Fundamentals, and Adoption [0.29465623430708915]
  We first describe the relation between discrete logarithms and two well-known asymmetric security schemes, RSA and Elliptic Curve Cryptography. Next, we present the foundations of lattice-based cryptography which is the bases of schemes that are considered to be safe against attacks by quantum algorithms. Finally, we describe two such quantum-safe algorithms (Kyber and Dilithium) in more detail.
  arXiv  Detail & Related papers  (2024-05-20T09:05:56Z)
• Provably Secure Disambiguating Neural Linguistic Steganography [66.30965740387047]
  The segmentation ambiguity problem, which arises when using language models based on subwords, leads to occasional decoding failures. We propose a novel secure disambiguation method named SyncPool, which effectively addresses the segmentation ambiguity problem. SyncPool does not change the size of the candidate pool or the distribution of tokens and thus is applicable to provably secure language steganography methods.
  arXiv  Detail & Related papers  (2024-03-26T09:25:57Z)
• A new lightweight additive homomorphic encryption algorithm [0.0]
  This article describes a lightweight additive homomorphic algorithm with the same encryption and decryption keys. It reduces the computational cost of encryption and decryption from modular exponentiation to modular multiplication.
  arXiv  Detail & Related papers  (2023-12-12T05:12:20Z)
• Lightweight Public Key Encryption in Post-Quantum Computing Era [0.0]
  Confidentiality in our digital world is based on the security of cryptographic algorithms. In the course of technological progress with quantum computers, the protective function of common encryption algorithms is threatened. Our concept describes the transformation of a classical asymmetric encryption method to a modern complexity class.
  arXiv  Detail & Related papers  (2023-11-24T21:06:42Z)
• SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation [72.10931780019297]
  Existing watermarking algorithms are vulnerable to paraphrase attacks because of their token-level design. We propose SemStamp, a robust sentence-level semantic watermarking algorithm based on locality-sensitive hashing (LSH) Experimental results show that our novel semantic watermark algorithm is not only more robust than the previous state-of-the-art method on both common and bigram paraphrase attacks, but also is better at preserving the quality of generation.
  arXiv  Detail & Related papers  (2023-10-06T03:33:42Z)
• CipherSniffer: Classifying Cipher Types [0.0]
  We frame the decryption task as a classification problem. We first create a dataset of transpositions, substitutions, text reversals, word reversals, sentence shifts, and unencrypted text.
  arXiv  Detail & Related papers  (2023-06-13T20:18:24Z)
• A Gold Standard Dataset for the Reviewer Assignment Problem [117.59690218507565]
  "Similarity score" is a numerical estimate of the expertise of a reviewer in reviewing a paper. Our dataset consists of 477 self-reported expertise scores provided by 58 researchers. For the task of ordering two papers in terms of their relevance for a reviewer, the error rates range from 12%-30% in easy cases to 36%-43% in hard cases.
  arXiv  Detail & Related papers  (2023-03-23T16:15:03Z)
• Stealing the Decoding Algorithms of Language Models [56.369946232765656]
  A key component of generating text from modern language models (LM) is the selection and tuning of decoding algorithms. In this work, we show, for the first time, that an adversary with typical API access to an LM can steal the type and hyper parameters of its decoding algorithms. Our attack is effective against popular LMs used in text generation APIs, including GPT-2, GPT-3 and GPT-Neo.
  arXiv  Detail & Related papers  (2023-03-08T17:15:58Z)
• Language Model Decoding as Likelihood-Utility Alignment [54.70547032876017]
  We introduce a taxonomy that groups decoding strategies based on their implicit assumptions about how well the model's likelihood is aligned with the task-specific notion of utility. Specifically, by analyzing the correlation between the likelihood and the utility of predictions across a diverse set of tasks, we provide the first empirical evidence supporting the proposed taxonomy.
  arXiv  Detail & Related papers  (2022-10-13T17:55:51Z)
• Enhancing Networking Cipher Algorithms with Natural Language [0.0]
  Natural language processing is considered as the weakest link in a networking encryption model. This paper summarizes how languages can be integrated into symmetric encryption as a way to assist in the encryption of vulnerable streams.
  arXiv  Detail & Related papers  (2022-06-22T09:05:52Z)
• Faster Secure Data Mining via Distributed Homomorphic Encryption [108.77460689459247]
  Homomorphic Encryption (HE) is receiving more and more attention recently for its capability to do computations over the encrypted field. We propose a novel general distributed HE-based data mining framework towards one step of solving the scaling problem. We verify the efficiency and effectiveness of our new framework by testing over various data mining algorithms and benchmark data-sets.
  arXiv  Detail & Related papers  (2020-06-17T18:14:30Z)

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.