Systematic Word Selection for Information Literacy and Security

Information literacy involves not just finding data, but also organising and presenting it in ways that are efficient and easy to understand. One useful exercise is generating unrelated word sets from A to Z. This technique is often used in security for passphrases, where high entropy (randomness) is required to ensure a system remains secure.

Selection Criteria

When building a word list for personal or public use, several factors should be considered to ensure the information is high-quality:

• Unrelatedness: Each word should belong to a different category or domain to prevent easy guessing or pattern recognition.
• Tone: Favouring positive or neutral words creates a better user experience and avoids negative bias in digital environments.
• Clarity: Words should be easy to spell and distinguish, especially if they are being used for human-readable security keys.

Application in Cryptography

In asymmetric encryption, we use two types of keys. Choosing specific words to represent these roles helps in understanding their function:

1. Private Keys (The "Secret" Factor)

A private key must be kept confidential and is the only tool that can decrypt data. Suitable words for this role include:

• Decisive: It is the final factor in unlocking data.
• Secret: It is hidden from everyone except the owner.
• Pinnacle: It represents the highest level of control.

2. Public Keys (The "Shared" Factor)

A public key is distributed to everyone and is used to encrypt data or verify signatures. Suitable words include:

• Openness: It is available for public use.
• Verifiable: It allows others to check the authenticity of a message.
• Luminous: It is visible and clear to the network.

Sample A-Z Non-Negative Word List

This table provides a reference set of unrelated, positive, or neutral words that align with British English spelling conventions.

Summary

Generating these sets is a practical way to manage digital identity and improve literacy. By choosing words that are unrelated yet positive, we create systems that are both robust and human-centric.