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Related Experiment Video

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Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

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Encrypted audio dataset based on the Collatz conjecture.

Diego Renza¹, Sebastian Mendoza¹, Dora M Ballesteros L¹

¹Universidad Militar Nueva Granada, Colombia.

|November 1, 2019

Summary

This study introduces a novel audio encryption method using the Collatz conjecture, transforming speech recordings into unintelligible files. The encrypted audio exhibits distinct statistical properties compared to natural speech, enhancing information security.

Keywords:

Audio Collatz conjecture Cryptanalysis Dataset Encryption Privacy Security

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Area of Science:

Information Security
Cryptography
Signal Processing

Background:

Encryption is crucial for securing sensitive information.
Altering content to unintelligibility ensures only authorized access.
Novel encryption methods are needed for diverse data types like audio.

Purpose of the Study:

To demonstrate a new audio encryption technique.
To analyze the characteristics of encrypted audio data.
To compare encrypted audio properties with natural speech.

Main Methods:

Applied a Collatz conjecture-based encryption method.
Processed five hundred speech recordings (50 speakers, 10 messages).
Obtained five hundred encrypted audio files for analysis.

Main Results:

Encrypted audio shows a quasi-uniform spectrogram and repetitive histogram patterns.
Statistical analysis reveals average sample -0.4, std dev 0.55, Shannon entropy ~7.5.
Encrypted signals differ significantly from natural speech (e.g., Gaussian histogram, lower std dev).

Conclusions:

The Collatz conjecture provides a novel approach for audio encryption.
Encrypted audio signals exhibit unique, non-natural statistical properties.
This method offers a distinct alternative for securing audio data.