Computation of Cryptographic Keys from Face Biometrics
We outline cryptographic key-computation from biometric data based on error-tolerant transformation of continuous-valued face eigenprojections to zero-error bitstrings suitable for cryptographic applicability. Bio-hashing is based on iterated inner-products between pseudorandom and user-specific eig...
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creator | Goh, Alwyn Ngo, David C. L. |
description | We outline cryptographic key-computation from biometric data based on error-tolerant transformation of continuous-valued face eigenprojections to zero-error bitstrings suitable for cryptographic applicability. Bio-hashing is based on iterated inner-products between pseudorandom and user-specific eigenprojections, each of which extracts a single-bit from the face data. This discretisation is highly tolerant of data capture offsets, with same-user face data resulting in highly correlated bitstrings. The resultant user identification in terms of a small bitstring-set is then securely reduced to a single cryptographic key via Shamir secret-sharing. Generation of the pseudorandom eigenprojection sequence can be securely parameterised via incorporation of physical tokens. Tokenised bio-hashing is rigorously protective of the face data, with security comparable to cryptographic hashing of token and knowledge key-factors. Our methodology has several major advantages over conventional biometric analysis ie elimination of false accepts (FA) without unacceptable compromise in terms of more probable false rejects (FR), straightforward key-management, and cryptographically rigorous commitment of biometric data in conjunction with verification thereof. |
doi_str_mv | 10.1007/978-3-540-45184-6_1 |
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L.</creator><contributor>Lioy, Antonio ; Mazzocchi, Daniele</contributor><creatorcontrib>Goh, Alwyn ; Ngo, David C. L. ; Lioy, Antonio ; Mazzocchi, Daniele</creatorcontrib><description>We outline cryptographic key-computation from biometric data based on error-tolerant transformation of continuous-valued face eigenprojections to zero-error bitstrings suitable for cryptographic applicability. Bio-hashing is based on iterated inner-products between pseudorandom and user-specific eigenprojections, each of which extracts a single-bit from the face data. This discretisation is highly tolerant of data capture offsets, with same-user face data resulting in highly correlated bitstrings. The resultant user identification in terms of a small bitstring-set is then securely reduced to a single cryptographic key via Shamir secret-sharing. Generation of the pseudorandom eigenprojection sequence can be securely parameterised via incorporation of physical tokens. Tokenised bio-hashing is rigorously protective of the face data, with security comparable to cryptographic hashing of token and knowledge key-factors. Our methodology has several major advantages over conventional biometric analysis ie elimination of false accepts (FA) without unacceptable compromise in terms of more probable false rejects (FR), straightforward key-management, and cryptographically rigorous commitment of biometric data in conjunction with verification thereof.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 3540201858</identifier><identifier>ISBN: 9783540201854</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540451846</identifier><identifier>EISBN: 3540451846</identifier><identifier>DOI: 10.1007/978-3-540-45184-6_1</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Biometric Data ; Computer science; control theory; systems ; Computer systems and distributed systems. User interface ; Cryptography ; Exact sciences and technology ; Face Data ; False Reject ; Information, signal and communications theory ; Keystroke Dynamics ; Memory and file management (including protection and security) ; Memory organisation. Data processing ; Pseudorandom Generator ; Signal and communications theory ; Software ; Telecommunications and information theory</subject><ispartof>Communications and Multimedia Security. 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L.</creatorcontrib><title>Computation of Cryptographic Keys from Face Biometrics</title><title>Communications and Multimedia Security. Advanced Techniques for Network and Data Protection</title><description>We outline cryptographic key-computation from biometric data based on error-tolerant transformation of continuous-valued face eigenprojections to zero-error bitstrings suitable for cryptographic applicability. Bio-hashing is based on iterated inner-products between pseudorandom and user-specific eigenprojections, each of which extracts a single-bit from the face data. This discretisation is highly tolerant of data capture offsets, with same-user face data resulting in highly correlated bitstrings. The resultant user identification in terms of a small bitstring-set is then securely reduced to a single cryptographic key via Shamir secret-sharing. Generation of the pseudorandom eigenprojection sequence can be securely parameterised via incorporation of physical tokens. Tokenised bio-hashing is rigorously protective of the face data, with security comparable to cryptographic hashing of token and knowledge key-factors. Our methodology has several major advantages over conventional biometric analysis ie elimination of false accepts (FA) without unacceptable compromise in terms of more probable false rejects (FR), straightforward key-management, and cryptographically rigorous commitment of biometric data in conjunction with verification thereof.</description><subject>Applied sciences</subject><subject>Biometric Data</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Cryptography</subject><subject>Exact sciences and technology</subject><subject>Face Data</subject><subject>False Reject</subject><subject>Information, signal and communications theory</subject><subject>Keystroke Dynamics</subject><subject>Memory and file management (including protection and security)</subject><subject>Memory organisation. Data processing</subject><subject>Pseudorandom Generator</subject><subject>Signal and communications theory</subject><subject>Software</subject><subject>Telecommunications and information theory</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540201858</isbn><isbn>9783540201854</isbn><isbn>9783540451846</isbn><isbn>3540451846</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2003</creationdate><recordtype>book_chapter</recordtype><recordid>eNotkD1PwzAURc2XRCn9BSxZGA1-ebZjjxBRQFRigdlynLgEmjqyw9B_j9vyliude_WGQ8gNsDtgrLrXlaJIBWeUC1CcSgMnZJEpZnZA8pTMQAJQRK7PyNW-KBkooc7JjCErqa44XpJFSt8sH5agkc-IrMMw_k526sO2CL6o426cwjra8at3xVu3S4WPYSiW1nXFYx-Gboq9S9fkwttN6hb_OSefy6eP-oWu3p9f64cVdajURL0FacG7EsC3wnHPRdtg0-kWWufB-haZQyEEaF1ipSSX3lkPqhFYMSFwTm6Pf0ebnN34aLeuT2aM_WDjzoCQmoEo8w6Ou5Sr7bqLpgnhJxlgZi_QZFUGTXZiDrZMFoh_jvVdsA</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Goh, Alwyn</creator><creator>Ngo, David C. L.</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2003</creationdate><title>Computation of Cryptographic Keys from Face Biometrics</title><author>Goh, Alwyn ; Ngo, David C. L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c388t-fa16a1fc211fd5c4f45db3be9d1dcf1afd30c35551992378646fcaf18b5370553</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Applied sciences</topic><topic>Biometric Data</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems and distributed systems. User interface</topic><topic>Cryptography</topic><topic>Exact sciences and technology</topic><topic>Face Data</topic><topic>False Reject</topic><topic>Information, signal and communications theory</topic><topic>Keystroke Dynamics</topic><topic>Memory and file management (including protection and security)</topic><topic>Memory organisation. Data processing</topic><topic>Pseudorandom Generator</topic><topic>Signal and communications theory</topic><topic>Software</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Goh, Alwyn</creatorcontrib><creatorcontrib>Ngo, David C. L.</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Goh, Alwyn</au><au>Ngo, David C. L.</au><au>Lioy, Antonio</au><au>Mazzocchi, Daniele</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Computation of Cryptographic Keys from Face Biometrics</atitle><btitle>Communications and Multimedia Security. Advanced Techniques for Network and Data Protection</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>2003</date><risdate>2003</risdate><spage>1</spage><epage>13</epage><pages>1-13</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540201858</isbn><isbn>9783540201854</isbn><eisbn>9783540451846</eisbn><eisbn>3540451846</eisbn><abstract>We outline cryptographic key-computation from biometric data based on error-tolerant transformation of continuous-valued face eigenprojections to zero-error bitstrings suitable for cryptographic applicability. Bio-hashing is based on iterated inner-products between pseudorandom and user-specific eigenprojections, each of which extracts a single-bit from the face data. This discretisation is highly tolerant of data capture offsets, with same-user face data resulting in highly correlated bitstrings. The resultant user identification in terms of a small bitstring-set is then securely reduced to a single cryptographic key via Shamir secret-sharing. Generation of the pseudorandom eigenprojection sequence can be securely parameterised via incorporation of physical tokens. Tokenised bio-hashing is rigorously protective of the face data, with security comparable to cryptographic hashing of token and knowledge key-factors. Our methodology has several major advantages over conventional biometric analysis ie elimination of false accepts (FA) without unacceptable compromise in terms of more probable false rejects (FR), straightforward key-management, and cryptographically rigorous commitment of biometric data in conjunction with verification thereof.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/978-3-540-45184-6_1</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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ispartof | Communications and Multimedia Security. Advanced Techniques for Network and Data Protection, 2003, p.1-13 |
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language | eng |
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source | Springer Books |
subjects | Applied sciences Biometric Data Computer science control theory systems Computer systems and distributed systems. User interface Cryptography Exact sciences and technology Face Data False Reject Information, signal and communications theory Keystroke Dynamics Memory and file management (including protection and security) Memory organisation. Data processing Pseudorandom Generator Signal and communications theory Software Telecommunications and information theory |
title | Computation of Cryptographic Keys from Face Biometrics |
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