{"title":"A TPRF-based pseudo-random number generator","authors":"Elena Andreeva, Andreas Weninger","doi":"10.20517/jsss.2023.45","DOIUrl":null,"url":null,"abstract":"Most cryptographic applications use randomness that is generated by pseudo-random number generators (PRNGs). A popular PRNG practical choice is the NIST standardized $$ \\rm{CTR\\_DRBG}$$ . In their recent ACNS 2023 publication, Andreeva and Weninger proposed a new and more efficient and secure PRNG called $$ \\mathtt{FCRNG}$$ . $$ \\mathtt{FCRNG}$$ is based on $$ \\rm{CTR\\_DRBG}$$ and uses the $$ n $$ -to-$$ 2n $$ forkcipher expanding primitive ForkSkinny as a building block. In this work, we create a new BKRNG PRNG, which is based on $$ \\mathtt{FCRNG}$$ and employs the novel $$ n $$ -to-$$ 8n $$ expanding primitive Butterknife. Butterknife is based on the Deoxys tweakable blockcipher (and thus AES) and realizes a tweakable expanding pseudo-random function. While both blockciphers and forkciphers are invertible primitives, tweakable expanding pseudo-random functions are not. This functional simplification enables security benefits for BKRNG in the robustness security game - the standard security goal for a PRNG. Contrary to the security bound of $$ \\rm{CTR\\_DRBG}$$ , we show that the security of our BKRNG construction does not degrade with the length of the random inputs, nor the number of requested output pseudo-random bits. We also empirically verify the BKRNG security with the NIST PRNG test suite and the TestU01 suite.\n Furthermore, we show the $$ n $$ -to-$$ 8n $$ multi-branch expanding nature of Butterknife contributes to a significant speed-up in the efficiency of BKRNG compared to $$ \\mathtt{FCRNG}$$ . More concretely, producing random bits with BKRNG is 30.0% faster than $$ \\mathtt{FCRNG}$$ and 49.2% faster than $$ \\rm{CTR\\_DRBG}$$ .","PeriodicalId":509397,"journal":{"name":"Journal of Surveillance, Security and Safety","volume":"31 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Surveillance, Security and Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20517/jsss.2023.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Most cryptographic applications use randomness that is generated by pseudo-random number generators (PRNGs). A popular PRNG practical choice is the NIST standardized $$ \rm{CTR\_DRBG}$$ . In their recent ACNS 2023 publication, Andreeva and Weninger proposed a new and more efficient and secure PRNG called $$ \mathtt{FCRNG}$$ . $$ \mathtt{FCRNG}$$ is based on $$ \rm{CTR\_DRBG}$$ and uses the $$ n $$ -to-$$ 2n $$ forkcipher expanding primitive ForkSkinny as a building block. In this work, we create a new BKRNG PRNG, which is based on $$ \mathtt{FCRNG}$$ and employs the novel $$ n $$ -to-$$ 8n $$ expanding primitive Butterknife. Butterknife is based on the Deoxys tweakable blockcipher (and thus AES) and realizes a tweakable expanding pseudo-random function. While both blockciphers and forkciphers are invertible primitives, tweakable expanding pseudo-random functions are not. This functional simplification enables security benefits for BKRNG in the robustness security game - the standard security goal for a PRNG. Contrary to the security bound of $$ \rm{CTR\_DRBG}$$ , we show that the security of our BKRNG construction does not degrade with the length of the random inputs, nor the number of requested output pseudo-random bits. We also empirically verify the BKRNG security with the NIST PRNG test suite and the TestU01 suite.
Furthermore, we show the $$ n $$ -to-$$ 8n $$ multi-branch expanding nature of Butterknife contributes to a significant speed-up in the efficiency of BKRNG compared to $$ \mathtt{FCRNG}$$ . More concretely, producing random bits with BKRNG is 30.0% faster than $$ \mathtt{FCRNG}$$ and 49.2% faster than $$ \rm{CTR\_DRBG}$$ .