NIST-Lite:能量受限平台上rng的随机性测试

Cheng-Yen Lee, K. Bharathi, Joellen S. Lansford, S. Khatri
{"title":"NIST-Lite:能量受限平台上rng的随机性测试","authors":"Cheng-Yen Lee, K. Bharathi, Joellen S. Lansford, S. Khatri","doi":"10.1109/ICCD53106.2021.00019","DOIUrl":null,"url":null,"abstract":"Random Number Generators (RNGs) are an essential part of many embedded applications and are used for security, encryption, and built-in test applications. The output of RNGs can be tested for randomness using the well-known NIST statistical test suite. Embedded applications using True Random Number Generators (TRNGs) need to test the randomness of their TRNGs periodically, because their randomness properties can drift over time. Using the full NIST test suite is unpracticed for this purpose, because the full NIST test suite is computationally intensive, and embedded systems (especially real-time systems) often have stringent constraints on the energy and runtime of the programs that are executed on them. In this paper, we propose novel algorithms to select the most effective subset of the NIST test suite, which works within specified runtime and energy budgets. To achieve this, we rank the NIST tests based on multiple metrics, including p-value/Time, p-value/Energy, p-value/Time2 and p-value/Energy2. Based on the total runtime or energy constraint specified by the user, our algorithms proceed to choose a subset of the NIST tests using this rank order. We call this subset of NIST tests as NIST-Lite. Our algorithms also take into account the runtime and energy required to generate the random sequences required (on the same platform) by the NIST-Lite tests. We evaluate the effectiveness of our method against the full NIST test suite (referred to as NIST-Full) and also against a greedily chosen subset of the NIST test suite (referred to as NIST-Greedy). We explore different variants of NIST-Lite. On average, using the same input sequences, the p-value obtained for the 4 best variants of NIST-Lite is 2× and 7× better than the p-value of NIST-Full and NIST-Greedy respectively. NIST-Lite also achieves 158× (204×) runtime (energy) reduction compared to the NIST-Full. Further, we study the performance of NIST-Lite and NIST-Full for deterministic (non-random) input sequences. For such sequences, the pass rate of the NIST-Lite tests is within 16% of the pass rate of NIST-Full on the same sequences, indicating that our NIST-Lite tests have a similar diagnostic ability as NIST-Full.","PeriodicalId":154014,"journal":{"name":"2021 IEEE 39th International Conference on Computer Design (ICCD)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"NIST-Lite: Randomness Testing of RNGs on an Energy-Constrained Platform\",\"authors\":\"Cheng-Yen Lee, K. Bharathi, Joellen S. Lansford, S. Khatri\",\"doi\":\"10.1109/ICCD53106.2021.00019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Random Number Generators (RNGs) are an essential part of many embedded applications and are used for security, encryption, and built-in test applications. The output of RNGs can be tested for randomness using the well-known NIST statistical test suite. Embedded applications using True Random Number Generators (TRNGs) need to test the randomness of their TRNGs periodically, because their randomness properties can drift over time. Using the full NIST test suite is unpracticed for this purpose, because the full NIST test suite is computationally intensive, and embedded systems (especially real-time systems) often have stringent constraints on the energy and runtime of the programs that are executed on them. In this paper, we propose novel algorithms to select the most effective subset of the NIST test suite, which works within specified runtime and energy budgets. To achieve this, we rank the NIST tests based on multiple metrics, including p-value/Time, p-value/Energy, p-value/Time2 and p-value/Energy2. Based on the total runtime or energy constraint specified by the user, our algorithms proceed to choose a subset of the NIST tests using this rank order. We call this subset of NIST tests as NIST-Lite. Our algorithms also take into account the runtime and energy required to generate the random sequences required (on the same platform) by the NIST-Lite tests. We evaluate the effectiveness of our method against the full NIST test suite (referred to as NIST-Full) and also against a greedily chosen subset of the NIST test suite (referred to as NIST-Greedy). We explore different variants of NIST-Lite. On average, using the same input sequences, the p-value obtained for the 4 best variants of NIST-Lite is 2× and 7× better than the p-value of NIST-Full and NIST-Greedy respectively. NIST-Lite also achieves 158× (204×) runtime (energy) reduction compared to the NIST-Full. Further, we study the performance of NIST-Lite and NIST-Full for deterministic (non-random) input sequences. For such sequences, the pass rate of the NIST-Lite tests is within 16% of the pass rate of NIST-Full on the same sequences, indicating that our NIST-Lite tests have a similar diagnostic ability as NIST-Full.\",\"PeriodicalId\":154014,\"journal\":{\"name\":\"2021 IEEE 39th International Conference on Computer Design (ICCD)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 39th International Conference on Computer Design (ICCD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCD53106.2021.00019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 39th International Conference on Computer Design (ICCD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD53106.2021.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

随机数生成器(rng)是许多嵌入式应用程序的重要组成部分,用于安全性、加密和内置测试应用程序。rng的输出可以使用著名的NIST统计测试套件来测试随机性。使用真随机数生成器(trng)的嵌入式应用程序需要定期测试其trng的随机性,因为它们的随机性属性可能随着时间的推移而漂移。使用完整的NIST测试套件是没有实践过的,因为完整的NIST测试套件是计算密集型的,嵌入式系统(尤其是实时系统)通常对在其上执行的程序的能量和运行时有严格的限制。在本文中,我们提出了新的算法来选择NIST测试套件中最有效的子集,该子集在指定的运行时间和能量预算内工作。为了实现这一点,我们基于多个指标对NIST测试进行排名,包括p-value/Time、p-value/Energy、p-value/Time2和p-value/Energy2。基于用户指定的总运行时间或能量约束,我们的算法继续使用这个排名顺序选择NIST测试的一个子集。我们把NIST测试的这个子集称为NIST- lite。我们的算法还考虑了生成NIST-Lite测试所需的随机序列(在同一平台上)所需的运行时间和能量。我们针对完整的NIST测试套件(称为NIST- full)以及NIST测试套件中贪婪选择的子集(称为NIST- greedy)来评估我们的方法的有效性。我们探索了NIST-Lite的不同变体。平均而言,在相同的输入序列下,NIST-Lite的4个最佳变体得到的p值分别比NIST-Full和NIST-Greedy的p值高2倍和7倍。与NIST-Full相比,NIST-Lite还实现了158倍(204倍)的运行时间(能量)减少。进一步,我们研究了NIST-Lite和NIST-Full对于确定性(非随机)输入序列的性能。对于这些序列,NIST-Lite测试的通过率与NIST-Full测试的通过率在16%以内,表明我们的NIST-Lite测试具有与NIST-Full相似的诊断能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
NIST-Lite: Randomness Testing of RNGs on an Energy-Constrained Platform
Random Number Generators (RNGs) are an essential part of many embedded applications and are used for security, encryption, and built-in test applications. The output of RNGs can be tested for randomness using the well-known NIST statistical test suite. Embedded applications using True Random Number Generators (TRNGs) need to test the randomness of their TRNGs periodically, because their randomness properties can drift over time. Using the full NIST test suite is unpracticed for this purpose, because the full NIST test suite is computationally intensive, and embedded systems (especially real-time systems) often have stringent constraints on the energy and runtime of the programs that are executed on them. In this paper, we propose novel algorithms to select the most effective subset of the NIST test suite, which works within specified runtime and energy budgets. To achieve this, we rank the NIST tests based on multiple metrics, including p-value/Time, p-value/Energy, p-value/Time2 and p-value/Energy2. Based on the total runtime or energy constraint specified by the user, our algorithms proceed to choose a subset of the NIST tests using this rank order. We call this subset of NIST tests as NIST-Lite. Our algorithms also take into account the runtime and energy required to generate the random sequences required (on the same platform) by the NIST-Lite tests. We evaluate the effectiveness of our method against the full NIST test suite (referred to as NIST-Full) and also against a greedily chosen subset of the NIST test suite (referred to as NIST-Greedy). We explore different variants of NIST-Lite. On average, using the same input sequences, the p-value obtained for the 4 best variants of NIST-Lite is 2× and 7× better than the p-value of NIST-Full and NIST-Greedy respectively. NIST-Lite also achieves 158× (204×) runtime (energy) reduction compared to the NIST-Full. Further, we study the performance of NIST-Lite and NIST-Full for deterministic (non-random) input sequences. For such sequences, the pass rate of the NIST-Lite tests is within 16% of the pass rate of NIST-Full on the same sequences, indicating that our NIST-Lite tests have a similar diagnostic ability as NIST-Full.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Smart-DNN: Efficiently Reducing the Memory Requirements of Running Deep Neural Networks on Resource-constrained Platforms CoRe-ECO: Concurrent Refinement of Detailed Place-and-Route for an Efficient ECO Automation Accurate and Fast Performance Modeling of Processors with Decoupled Front-end Block-LSM: An Ether-aware Block-ordered LSM-tree based Key-Value Storage Engine Dynamic File Cache Optimization for Hybrid SSDs with High-Density and Low-Cost Flash Memory
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1