一种新的基于转换生物特征的公钥加密模型

Bin Yan, Lin You
{"title":"一种新的基于转换生物特征的公钥加密模型","authors":"Bin Yan, Lin You","doi":"10.1109/DESEC.2017.8073861","DOIUrl":null,"url":null,"abstract":"In the fuzzy identity-based encryption scheme, a trusted KGC (key generation center) is needed to generate the corresponding private key corresponding to the user's biometric public key. In order to deal with the decentralization problem and the verification problem of the users identity, we propose a public key encryption model based on transformed biometrics. In this model, the user uses the transformed biometrics as his public key and his inherent real biometrics as his private key. In order to protect the user's biometrics information from being leaked, we take some appropriate security measures such as biometric template protection technology and irreversible random conversion technology. These operations are performed locally by the user, and once the public key is generated, the random transformation matrix is deleted or destroyed. The user connects the device serial number in parallel with the modulus N as the input value of the SHA-256 function and uses the output message digest as the public information. The user uses the inner product encryption to complete the encryption process. In this model, the security parameter and the private keys do not require any trusted organization for their generation, and these sensitive information does not need to be transmitted over a public network. The communication parties do not need to know the public key information of the other party in advance. When the user needs to transmit the secret message, the user can query the corresponding public key and related information. We have effectively linked the biological identities with the digital identities. Our thorough analysis shows that the proposed encryption model is both secure and efficient for an encryption algorithm.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"25 1","pages":"424-428"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A novel public key encryption model based on transformed biometrics\",\"authors\":\"Bin Yan, Lin You\",\"doi\":\"10.1109/DESEC.2017.8073861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the fuzzy identity-based encryption scheme, a trusted KGC (key generation center) is needed to generate the corresponding private key corresponding to the user's biometric public key. In order to deal with the decentralization problem and the verification problem of the users identity, we propose a public key encryption model based on transformed biometrics. In this model, the user uses the transformed biometrics as his public key and his inherent real biometrics as his private key. In order to protect the user's biometrics information from being leaked, we take some appropriate security measures such as biometric template protection technology and irreversible random conversion technology. These operations are performed locally by the user, and once the public key is generated, the random transformation matrix is deleted or destroyed. The user connects the device serial number in parallel with the modulus N as the input value of the SHA-256 function and uses the output message digest as the public information. The user uses the inner product encryption to complete the encryption process. In this model, the security parameter and the private keys do not require any trusted organization for their generation, and these sensitive information does not need to be transmitted over a public network. The communication parties do not need to know the public key information of the other party in advance. When the user needs to transmit the secret message, the user can query the corresponding public key and related information. We have effectively linked the biological identities with the digital identities. Our thorough analysis shows that the proposed encryption model is both secure and efficient for an encryption algorithm.\",\"PeriodicalId\":92346,\"journal\":{\"name\":\"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...\",\"volume\":\"25 1\",\"pages\":\"424-428\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DESEC.2017.8073861\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DESEC.2017.8073861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

在基于模糊身份的加密方案中,需要一个可信的密钥生成中心(KGC)来生成与用户的生物特征公钥相对应的私钥。为了解决去中心化问题和用户身份验证问题,提出了一种基于转换生物特征的公钥加密模型。在该模型中,用户使用转换后的生物特征作为公钥,使用其固有的真实生物特征作为私钥。为了保护用户的生物特征信息不被泄露,我们采取了一些适当的安全措施,如生物特征模板保护技术和不可逆随机转换技术。这些操作由用户在本地执行,一旦生成公钥,将删除或销毁随机转换矩阵。用户将设备序列号与模数N并行连接,作为SHA-256功能的输入值,并将输出的消息摘要作为公开信息。用户使用内积加密完成加密过程。在这个模型中,安全参数和私钥的生成不需要任何受信任的组织,这些敏感信息也不需要通过公共网络传输。通信双方不需要事先知道对方的公钥信息。当用户需要传输保密消息时,可以查询到相应的公钥和相关信息。我们已经有效地将生物身份与数字身份联系起来。我们的全面分析表明,所提出的加密模型对于加密算法来说既安全又有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel public key encryption model based on transformed biometrics
In the fuzzy identity-based encryption scheme, a trusted KGC (key generation center) is needed to generate the corresponding private key corresponding to the user's biometric public key. In order to deal with the decentralization problem and the verification problem of the users identity, we propose a public key encryption model based on transformed biometrics. In this model, the user uses the transformed biometrics as his public key and his inherent real biometrics as his private key. In order to protect the user's biometrics information from being leaked, we take some appropriate security measures such as biometric template protection technology and irreversible random conversion technology. These operations are performed locally by the user, and once the public key is generated, the random transformation matrix is deleted or destroyed. The user connects the device serial number in parallel with the modulus N as the input value of the SHA-256 function and uses the output message digest as the public information. The user uses the inner product encryption to complete the encryption process. In this model, the security parameter and the private keys do not require any trusted organization for their generation, and these sensitive information does not need to be transmitted over a public network. The communication parties do not need to know the public key information of the other party in advance. When the user needs to transmit the secret message, the user can query the corresponding public key and related information. We have effectively linked the biological identities with the digital identities. Our thorough analysis shows that the proposed encryption model is both secure and efficient for an encryption algorithm.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信