Format-preserving-encryption as pseudo random number generator in practice

During many years of work in the industry, we have often encountered the problem of generating a large quantity of unique pseudo-random numbers. In this paper, we describe the challenges of generating a large quantity of unique pseudo-random numbers and propose a new approach to address this issue. Our proposed method uses Format Preserving Encryption (FPE) algorithms, which solve the problem of pre-generating a large number of numbers and verifying whether a newly generated number has already been generated. Ultimately, we found that generating such numbers using FPE algorithms is faster than using system functions to generate pseudo-random numbers. However, this is not the most crucial advantage of this proposal. In the standard approach, the time required to generate new numbers increases exponentially as the pool of generated numbers grows. Our proposed approach using FPE algorithms solves this problem. In this work, we performed a quality check of our pseudo-random number generator using the Diehard Statistical Test Suite, demonstrating that all tests passed without issues.

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Publication Details

Journal
Automatika
Published
2025-10-02
DOI
https://doi.org/10.1080/00051144.2025.2587409
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
0.00
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article

Format-preserving-encryption as pseudo random number generator in practice

Automatika
Chaos-based Image/Signal Encryption
article

Format-preserving-encryption as pseudo random number generator in practice

article en

Abstract

During many years of work in the industry, we have often encountered the problem of generating a large quantity of unique pseudo-random numbers. In this paper, we describe the challenges of generating a large quantity of unique pseudo-random numbers and propose a new approach to address this issue. Our proposed method uses Format Preserving Encryption (FPE) algorithms, which solve the problem of pre-generating a large number of numbers and verifying whether a newly generated number has already been generated. Ultimately, we found that generating such numbers using FPE algorithms is faster than using system functions to generate pseudo-random numbers. However, this is not the most crucial advantage of this proposal. In the standard approach, the time required to generate new numbers increases exponentially as the pool of generated numbers grows. Our proposed approach using FPE algorithms solves this problem. In this work, we performed a quality check of our pseudo-random number generator using the Diehard Statistical Test Suite, demonstrating that all tests passed without issues.

AutomatikaVol. 66(4)
University of Zagreb (HR)
Industry, innovation and infrastructure
Openalex Percentile: Top 42%
Chaos-based Image/Signal Encryption
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