We outline cryptographic key-computation from biometric data based on error-tolerant transformation of continuous-valued face eigenprojec- tions 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 analy- sis 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.
['Alwyn Goh', 'David Chek Ling Ngo']
Computation of Cryptographic Keys from Face Biometrics