基于SRAM物理不可克隆函數(shù)的高效真隨機(jī)種子發(fā)生器設(shè)計(jì)
發(fā)布時間:2018-01-20 18:44
本文關(guān)鍵詞: 物理不可克隆函數(shù) 噪聲節(jié)點(diǎn) 真隨機(jī)種子 高效率 出處:《電子與信息學(xué)報》2017年06期 論文類型:期刊論文
【摘要】:該文設(shè)計(jì)了一種基于SRAM物理不可克隆函數(shù)(PUFs)的高效真隨機(jī)種子發(fā)生器。通過將不提供熵值的穩(wěn)定節(jié)點(diǎn)和提供低熵值的噪聲節(jié)點(diǎn)篩除,只選用能夠提供較高熵值的噪聲節(jié)點(diǎn)來生成滿熵種子,大幅降低需要處理的數(shù)據(jù)量,提高節(jié)點(diǎn)數(shù)據(jù)的處理效率。通過測試SRAM PUFs內(nèi)部噪聲節(jié)點(diǎn)的振蕩特性,提出篩選出SRAM PUFs內(nèi)部高熵值的噪聲節(jié)點(diǎn)的最佳策略,最終基于此策略設(shè)計(jì)出真隨機(jī)種子發(fā)生器。該設(shè)計(jì)可以產(chǎn)生128~256 bit長度的滿熵的種子且處理的節(jié)點(diǎn)數(shù)據(jù)量只有當(dāng)前方法的0.5%~4%。生成的種子滿足NIST架構(gòu)的隨機(jī)數(shù)生成器要求,產(chǎn)生的偽隨機(jī)數(shù)全部通過了隨機(jī)數(shù)檢測。與現(xiàn)有設(shè)計(jì)相比,該文提出的真隨機(jī)種子發(fā)生器是一種高效的、適用范圍較廣的設(shè)計(jì)。
[Abstract]:In this paper, an efficient true random seed generator based on SRAM physical nonclonal function (PUFs) is designed, which removes the stable nodes without entropy and the noise nodes with low entropy. Only the noise nodes which can provide high entropy value are used to generate full entropy seeds, which greatly reduce the amount of data to be processed. By testing the oscillation characteristics of SRAM PUFs internal noise nodes, the optimal strategy of selecting the noise nodes with high entropy value in SRAM PUFs is put forward. Finally, a true random seed generator is designed based on this strategy. The full entropy seed of bit length and the amount of node data processed are only 0.5% of the current method. The generated seeds meet the requirements of the random number generator of the NIST architecture. All the pseudo-random numbers are tested by random number. Compared with the existing design, the true random seed generator presented in this paper is an efficient and widely used design.
【作者單位】: 東南大學(xué)集成電路學(xué)院;深圳大學(xué)信息工程學(xué)院;
【基金】:國家自然科學(xué)基金(61571116)~~
【分類號】:TN402;TN918
【正文快照】: 1引言在當(dāng)今社會,信息安全的問題日益被人們關(guān)注。物理不可克隆函數(shù)(Physical Unclonable Functions,PUFs)[1]作為其中重要的組成部分,被越來越多的研究者所研究。SRAM PUFs因其擁有設(shè)計(jì)簡單、經(jīng)濟(jì)性好、可靠性較高[2]等特點(diǎn)而廣受青睞。無論是身份認(rèn)證[3,4]、隨機(jī)數(shù)產(chǎn)生[5]還,
本文編號:1449188
本文鏈接:http://sikaile.net/kejilunwen/xinxigongchenglunwen/1449188.html
最近更新
教材專著