AdaCrypt - Vector Cryptography




Worked Example
& Other General
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Ciphers as One-Way Function Synthesising

Introduction

Vector Cryptography
& Scalar Cryptography

Anatomy of a Vector Cipher (Sourcecode 1)

Anatomy of a Vector Cipher (Sourcecode 2)

Anatomy of a Vector Cipher (Sourcecode 3)

Anatomy of a Vector Cipher (Sourcecode 4)

Operational Overview

Crypto Entropy

Resume of Entropy
in Cryptography

Entropy Balances
in Cryptography

Entropy and Structure
in Cryptography

Unicode and ASCII
in Cryptography

Raw Encryption
Data Foundations

Alice's Database Management

Alice Encrypts
- Bob Decrypts

USB's, Flash Memory
& Encryption

A Graphical Demonstration

The Network

Polyalphabets

Inverse Function

Lumpy Data
and Randomness

Factoring Very Large
Numbers by GPS

ASCII Modulated
Vigenere Cryptography

ASCII Modulated
Vigenere & Sourcecode

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Resume of Entropy in Cryptography 

Entropy and The Significance of Raw Encryption Data Types in Cryptography.

Scalar Cryptography is being so called here because it uses scalar methods on scalar data (numbers) during encryption transformations.

Vector Cryptography is being so called here because it uses vector methods on both scalar and vector data during encryption transformations.

Entropy is a handy word being bandied about a lot these days with a different definition in each case of its application. It is even used by journalists to assign quality to musical performances and drama reviews. Its main and only use once upon a time was in the science of thermodynamics but nobody has a lien on words so why shouldn’t it be used in any other context also, so it is “welcome” to entropy in cryptography. It largely means disorder in this context. Mr Claude Shannon has written about its application to information theory. I quote : “In information theory, the Shannon entropy or information entropy is a measure of the uncertainty associated with a random variable.” ( copied from Wikipedia)

This is very nicely expressed by Mr Shannon and indeed worthy of remembering as a unit of entropy.- Shannon entropy. This is something however to be seen as a unitising exercise that has wider ramifications than just ciphers and cryptography and is perhaps a topic apart in information technology.

As applied to cryptography this is how the writer sees information entropy.

Data + Structure = Information ( to the illegal cryptanalyst)

No Structure means no information.

It is best understood that information entropy is the negative of structure. So,

Data + Structure + entropy = Information (Leakage from the ciphertext)

Make enthropy = structure and there is no information (for Eve => eavesdropper)

The whole purpose of cryptography then is to inject enough entropy into ciphertext to prevent it having discernible, readable structure that may reveal the original plaintext. A cipher then must be able to provide enough entropy to (ideally) totally negate the innate structure of the raw untransformed encryption data (Structure in the Ciphertext equation outlined above) for maximum security. Bob of course replaces it all during decryption.

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AdaCrypt Vector Cryptography ® 2003 Austin O'Byrne