Investigating Optimal Feedback Functions of Second Degree for Nonlinear Feedback Shift Registers Using Computer-Based Tools

Nonlinear feedback shift registers (NLFSRs) are reliable tools for generating pseudorandom bits. Due to their efficiency and high security, NLFSRs are very important components in many security applications, such as network protocols and blockchains. NLFSRs are known to be more secure than linear feedback shift registers. However, it is difficult to obtain their optimal feedback functions due to the lack of a mathematical basis for NLFSRs. The paper presents computer-based tools for investigating optimal feedback functions of second degree for nonlinear feedback shift registers. The tools are used in the educational process in the course “Telecommunication Security” for the 7th-semester students in the specialty “Internet and Mobile Communications” at the University of Ruse “Angel Kanchev”.

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Published
2024-10-16
DOI
https://doi.org/10.1109/siitme63973.2024.10814793
Primary Topic
Neural Networks and Applications
Type
article
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article

Investigating Optimal Feedback Functions of Second Degree for Nonlinear Feedback Shift Registers Using Computer-Based Tools

Адриана Бороджиева
Neural Networks and Applications
article

Investigating Optimal Feedback Functions of Second Degree for Nonlinear Feedback Shift Registers Using Computer-Based Tools

Адриана Бороджиева
article en

Abstract

Nonlinear feedback shift registers (NLFSRs) are reliable tools for generating pseudorandom bits. Due to their efficiency and high security, NLFSRs are very important components in many security applications, such as network protocols and blockchains. NLFSRs are known to be more secure than linear feedback shift registers. However, it is difficult to obtain their optimal feedback functions due to the lack of a mathematical basis for NLFSRs. The paper presents computer-based tools for investigating optimal feedback functions of second degree for nonlinear feedback shift registers. The tools are used in the educational process in the course “Telecommunication Security” for the 7th-semester students in the specialty “Internet and Mobile Communications” at the University of Ruse “Angel Kanchev”.

Angel Kanchev University of Ruse (BG)
Openalex Percentile: Top 78%
Neural Networks and Applications
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