Cryptographic Key Generation from Biometric Data Using Lattice Mapping
Crypto-biometric systems are recently emerging as an effective process of key management to address the security weakness of conventional key release systems using pass-codes, tokens or pattern recognition based biometrics. This paper presents a lattice mapping based fuzzy commitment method for cryp...
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| creator | Gang Zheng Wanqing Li Ce Zhan |
| description | Crypto-biometric systems are recently emerging as an effective process of key management to address the security weakness of conventional key release systems using pass-codes, tokens or pattern recognition based biometrics. This paper presents a lattice mapping based fuzzy commitment method for cryptographic key generation from biometric data. The proposed method not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker. Simulated results have demonstrated that its authentication accuracy is comparable to the well-known k-nearest neighbour classification |
| doi_str_mv | 10.1109/ICPR.2006.423 |
| format | Conference Proceeding |
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This paper presents a lattice mapping based fuzzy commitment method for cryptographic key generation from biometric data. The proposed method not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker. 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Simulated results have demonstrated that its authentication accuracy is comparable to the well-known k-nearest neighbour classification</description><subject>Authentication</subject><subject>Binary sequences</subject><subject>Bioinformatics</subject><subject>Biometrics</subject><subject>Cryptography</subject><subject>Data security</subject><subject>Error correction codes</subject><subject>Information security</subject><subject>Lattices</subject><subject>Pattern recognition</subject><issn>1051-4651</issn><issn>2831-7475</issn><isbn>0769525210</isbn><isbn>9780769525211</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjMtOwzAQRS0eEqF0yYqNfyDB49hxvITQloogEKLrapJMihF5yPEmf08kOJujqyNdxm5BJADC3u-L949ECpElSqZnLJJ5CrFRRp-za2Eyq6WWIC5YBEJDrDINV2w9Td9iQWmtpI3YtvDzGIaTx_HL1fyFZr6jnjwGN_S89UPHH93QUfBLfcKA_DC5_sRLDMHVxF9xHJd9wy5b_Jlo_e8VO2w3n8VzXL7t9sVDGdcSbIjzVMgmRwsVyMYY0xCSrbSqLGb5QiPRNBXlKBRhpbK6Rr1ksKKCtpE6XbG7v19HRMfRuw79fITM2txC-gv9HEz3</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Gang Zheng</creator><creator>Wanqing Li</creator><creator>Ce Zhan</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2006</creationdate><title>Cryptographic Key Generation from Biometric Data Using Lattice Mapping</title><author>Gang Zheng ; Wanqing Li ; Ce Zhan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c219t-8302d8a91b12d777deae9b54b9a68888d2a7dbe8a04eab46cca5b54190b1fd253</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Authentication</topic><topic>Binary sequences</topic><topic>Bioinformatics</topic><topic>Biometrics</topic><topic>Cryptography</topic><topic>Data security</topic><topic>Error correction codes</topic><topic>Information security</topic><topic>Lattices</topic><topic>Pattern recognition</topic><toplevel>online_resources</toplevel><creatorcontrib>Gang Zheng</creatorcontrib><creatorcontrib>Wanqing Li</creatorcontrib><creatorcontrib>Ce Zhan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gang Zheng</au><au>Wanqing Li</au><au>Ce Zhan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Cryptographic Key Generation from Biometric Data Using Lattice Mapping</atitle><btitle>18th International Conference on Pattern Recognition (ICPR'06)</btitle><stitle>ICPR</stitle><date>2006</date><risdate>2006</risdate><volume>4</volume><spage>513</spage><epage>516</epage><pages>513-516</pages><issn>1051-4651</issn><eissn>2831-7475</eissn><isbn>0769525210</isbn><isbn>9780769525211</isbn><abstract>Crypto-biometric systems are recently emerging as an effective process of key management to address the security weakness of conventional key release systems using pass-codes, tokens or pattern recognition based biometrics. This paper presents a lattice mapping based fuzzy commitment method for cryptographic key generation from biometric data. The proposed method not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker. Simulated results have demonstrated that its authentication accuracy is comparable to the well-known k-nearest neighbour classification</abstract><pub>IEEE</pub><doi>10.1109/ICPR.2006.423</doi><tpages>4</tpages></addata></record> |
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| ispartof | 18th International Conference on Pattern Recognition (ICPR'06), 2006, Vol.4, p.513-516 |
| issn | 1051-4651 2831-7475 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Authentication Binary sequences Bioinformatics Biometrics Cryptography Data security Error correction codes Information security Lattices Pattern recognition |
| title | Cryptographic Key Generation from Biometric Data Using Lattice Mapping |
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