https://github.com/arr4n/csharp-chaoticcipher

A stream cipher utilising pluggable, chaotic, non-linear systems as PRNGs
https://github.com/arr4n/csharp-chaoticcipher

Last synced: 27 days ago
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A stream cipher utilising pluggable, chaotic, non-linear systems as PRNGs

• Host: GitHub
• URL: https://github.com/arr4n/csharp-chaoticcipher
• Owner: ARR4N
• Created: 2011-05-01T06:08:03.000Z (almost 14 years ago)
• Default Branch: master
• Last Pushed: 2011-05-16T10:50:54.000Z (over 13 years ago)
• Last Synced: 2024-11-09T22:34:29.450Z (3 months ago)
• Language: C#
• Homepage:
• Size: 250 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README
  • License: License-gpl-3.0.txt

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README

        
Copyright 2011 Arran Schlosberg (http://arranschlosberg.com);

This file is part of CSharp-ChaoticCipher (https://github.com/aschlosberg/CSharp-ChaoticCipher).

    CSharp-ChaoticCipher is free software: you can redistribute it and/or modify

    it under the terms of the GNU General Public License as published by

    the Free Software Foundation, either version 3 of the License, or

    (at your option) any later version.

    CSharp-ChaoticCipher is distributed in the hope that it will be useful,

    but WITHOUT ANY WARRANTY; without even the implied warranty of

    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License

    along with CSharp-ChaoticCipher.  If not, see .

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Usage: ./ChaoticCipher.exe (enc|dec) infile outfile [MAClength=64]

Under correct circumstances, particular non-linear dynamical systems display chaotic behaviour. A characteristic of chaotic behaviour is the sensitivity to initial conditions, i.e. perturbations to the state of the system will, no matter how small, eventually "yield widely diverging outcomes... rendering long-term prediction impossible in general". "Things become worse when the deterministic component is a non-linear feedback system." This can be utilised to generate a deterministic PRNG by reading the least significant bit of a chaotic system after a set number of iterations.

While most explanations concentrate on sensitivity to initial conditions the concept can logically be extended to include sensitivity to minor perturbations (referred to as "nudges" in the code). For example, nudging the primary arm of a double pendulum (see examples link below) will greatly alter the stream of random bits provided by the associated PRNG. A stream of data can be used to nudge the system at each iteration. This cipher utilises 3 main sources for perturbations (each nudge = 1 byte):

* Symmetric encryption key - hashed using SHA512 - 64 nudges

* Initiliasation vector (IV) - 64 bytes sourced from System.Security.Cryptography.RNGCryptoServiceProvider - 64 nudges

* Plaintext bytestream - using the same key and IV will still result in a different PRNG stream

* Identically-initialised, parallel chaotic systems - the least significant bits of one are used to nudge the next - increased feedback

The plaintext byte used for nudging is delayed such that the nudge byte is the one immediately after the one being enc/deciphered. This is a theoretical necessity when in decipher mode to allow the plaintext to be recovered before being used as the nudger for the next iteration.

Use of the plaintext stream creates an implicit authentication scheme in that a change to the ciphertext will result in a change to the derived plaintext and hence a change to the PRNG output. An explicit MAC based on this appends a series of (MACLength) null bytes to the end of the plaintext.

XORing of the PRNG stream with the plain/ciphertext stream provides the relevant output of cipher/plaintext. This allows enc/deciphering to be done with the same function.

For testing and proof-of-concept, a simple Lorenzian water wheel model implements the NonLinearSystem class. Nudges are used for the filling volume of the relevant bucket.

See:

* http://en.wikipedia.org/wiki/Chaos_theory

* Examples of chaotic systems - http://en.wikipedia.org/wiki/Chaos_theory#See_also

* http://en.wikipedia.org/wiki/Stream_cipher

* http://www.ace.gatech.edu/experiments2/2413/lorenz/fall02/

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It is important to note that this code simply provides a framework for utilising models of chaotic systems. The security of the resulting stream cipher is determined by the characteristics of the system used.

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