Scalable Nonlinear Sequence Generation using Composite Mersenne Product Registers
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Abstract
We introduce a novel composition method that combines linear feedback registers into larger nonlinear structures and generalizes earlier methods such as cascade connections. We prove a Chaining Period Theorem which provides the cycle structure of these register constructions. We then use this Chaining Period Theorem and a new construction we call a Product Register (PR) to introduce a flexible and scalable register family with desirable properties, which we term Composite Mersenne Product Registers (CMPRs). We provide an algorithm to estimate the linear complexity of a chosen CMPR and investigate the statistical properties and security of a CMPR-based pseudorandom generator. Finally, we propose a family of CMPR-based stream ciphers and provide comparisons with the TRIVIUM stream cipher in terms of hardware area and security.
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David Gordon, Arman Allahverdi, Simon Abrelat, Anna Hemingway, Adil Farooq, Isabella Smith, Nitya Arora, Allen Ian Chang, Yongyu Qiang, and Vincent John Mooney III, Scalable Nonlinear Sequence Generation using Composite Mersenne Product Registers. IACR Communications in Cryptology, vol. 1, no. 4, Jan 13, 2025, doi: 10.62056/a3tx11zn4.
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This work is licensed under a Creative Commons Attribution (CC BY) license.