気象データとLFSRによる乱数生成手法の評価

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2023/02/01

タイトル(英語): Evaluation of Random Number Generator Utilizing Weather Data and LFSR

著者名: 千葉　歩武（豊橋技術科学大学 電気・電子情報工学課程），市川　周一（豊橋技術科学大学 電気・電子情報工学系）

著者名(英語): Ayumu Chiba (Electrical and Electronic Information Engineering Course, Toyohashi University of Technology), Shuichi Ichikawa (Department Electrical and Electronic Information Engineering, Toyohashi University of Technology)

キーワード: 乱数，URNG，TRNG，LFSR　　random number，URNG，TRNG，LFSR

要約(英語): Entropy sources (e.g., physical phenomena) are essential for true random number (TRN) generation. An unpredictable random number (URN) generator was previously proposed, which uses processor internal registers as its entropy sources. Another study proposed to integrate a linear feedback shift register (LFSR) in a processor, and sample it to generate a URN sequence. The entropy source of this URN is the fluctuation of sampling period. The current study proposes to use weather data as the entropy source for URN generation, where the sampling period is modified by the wind direction data. The derived URN sequences passed the Diehard test when the least sampling period β > 29 with a 32-bit LFSR. It also passed the NIST test when the weather data were accessed with an appropriate hash function when β was 32.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.143 No.2 （2023） 特集：ドローンとロボット組み込み/サスティナブルシステム

本誌掲載ページ: 80-86 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/143/2/143_80/_article/-char/ja/