Extending RC4 to Construct Secure Random Number Generators

Lih Yuan Deng, Dale Bowman, Ching Chi Yang, Horng-Shing Lu

研究成果: Conference contribution同行評審

摘要

We consider a general framework for constructing non-linear generators by adding a (32-bit or larger) pseudo-random number generator (PRNG) as a baseline generator to the basic RC4 design, in which an index-selection scheme similar to RC4 is used. We refer to the proposed design as the eRC (enhanced/extended RC4) design. We discuss several advantages of adding a good baseline generator to the RC4 design, including new updating schemes for the auxiliary table. We consider some popular PRNGs with the nice properties of high-dimensional equi-distribution, efficiency, long period, and portability as the baseline generator. We demonstrate that eRC generators are very efficient via extensive empirical testing on some eRC generators. We also show that eRC is flexible enough to choose minimal design parameters for eRC generators and yet the resulting eRC generators still pass stringent empirical tests, which makes them suitable for both software and hardware implementations.

原文English
主出版物標題Proceedings of the 2021 Annual Modeling and Simulation Conference, ANNSIM 2021
編輯Cristina Ruiz Martin, Maria Julia Blas, Alonso Inostrosa Psijas
發行者Institute of Electrical and Electronics Engineers Inc.
頁面263-274
頁數12
53
版本2
ISBN(電子)9781565553750
DOIs
出版狀態Published - 19 7月 2021
事件2021 Annual Modeling and Simulation Conference, ANNSIM 2021 - Virtual, Fairfax, United States
持續時間: 19 7月 202122 7月 2021

出版系列

名字Proceedings of the 2021 Annual Modeling and Simulation Conference, ANNSIM 2021

Conference

Conference2021 Annual Modeling and Simulation Conference, ANNSIM 2021
國家/地區United States
城市Virtual, Fairfax
期間19/07/2122/07/21

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