The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Combining Crypto with Biometrics Effectively
Open accessAbstract
We propose the first practical and secure way to integrate the iris biometric into cryptographic applications. A repeatable binary string, which we call a biometric key, is generated reliably from genuine iris codes. A well-known difficulty has been how to cope with the 10 to 20 percent of error bits within an iris code and derive an error-free key. To solve this problem, we carefully studied the error patterns within iris codes and devised a two-layer error correction technique that combines Hadamard and Reed-Solomon codes. The key is generated from a subject's iris image with the aid of auxiliary error-correction data, which do not reveal the key and can be saved in a tamper-resistant token, such as a smart card. The reproduction of the key depends on two factors: the iris biometric and the token. The attacker has to procure both of them to compromise the key. We evaluated our technique using iris samples from 70 different eyes, with 10 samples from each eye. We found that an error-free key can be reproduced reliably from genuine iris codes with a 99.5 percent success rate. We can generate up to 140 bits of biometric key, more than enough for 128-bit AES. The extraction of a repeatable binary string from biometrics opens new possible applications, where a strong binding is required between a person and cryptographic operations. For example, it is possible to identify individuals without maintaining a central database of biometric templates, to which privacy objections might be raised.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Theory of Error-Correcting Codes
(1977) · North-Holland Mathematical Library · doi:10.1016/s0924-6509(08)x7030-8 · Cited by 10,760
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data
Dodis, Y., Reyzin, L., & Smith, A. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24676-3_31 · Cited by 2,038
Juels, A., & Wattenberg, M. (1999) · Proceedings of the 6th ACM conference on Computer and communications security · doi:10.1145/319709.319714 · Cited by 1,591
The Theory of Information and Coding
McEliece, R. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9780511606267 · Cited by 986
The importance of being random: statistical principles of iris recognition
Daugman, J. (2003) · Pattern Recognition · doi:10.1016/s0031-3203(02)00030-4 · Cited by 951
Self-citationBiometric cryptosystems: issues and challenges
Uludag, U., Pankanti, S., Prabhakar, S., & Jain, A. K. (2004) · Proceedings of the IEEE · doi:10.1109/jproc.2004.827372 · Cited by 921
Juels, A., & Sudan, M. (2003) · Proceedings IEEE International Symposium on Information Theory, · doi:10.1109/isit.2002.1023680 · Cited by 820
The theory of error-correcting codes
Kung, J., & Rota, G.-C. (1979) · Advances in Mathematics · doi:10.1016/0001-8708(79)90034-3 · Cited by 550
Secure smartcardbased fingerprint authentication
Clancy, T. C., Kiyavash, N., & Lin, D. J. (2003) · Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications - WBMA '03 · doi:10.1145/982507.982516 · Cited by 482
Security Engineering: A Guide to Building Dependable Distributed Systems
Anderson, R. (2020) · doi:10.1002/9781119644682 · Cited by 345
Self-citation
Cited by
Image understanding for iris biometrics: A survey
Bowyer, K. W., Hollingsworth, K., & Flynn, P. J. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.08.005 · Cited by 907
Fingerprint-Based Fuzzy Vault: Implementation and Performance
Nandakumar, K., Jain, A. K., & Pankanti, S. (2007) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2007.908165 · Cited by 553
Secure and Robust Iris Recognition Using Random Projections and Sparse Representations
Pillai, J. K., Patel, V. M., Chellappa, R., & Ratha, N. K. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.34 · Cited by 324
Cancellable biometrics and annotations on biohash
Teoh, A. B. J., Kuan, Y. W., & Lee, S. (2008) · Pattern Recognition · doi:10.1016/j.patcog.2007.12.002 · Cited by 213
A survey on methods and challenges in EEG based authentication
Jalaly Bidgoly, A., Jalaly Bidgoly, H., & Arezoumand, Z. (2020) · Computers & Security · doi:10.1016/j.cose.2020.101788 · Cited by 173
Metadata
- Authors
- Hao, F., Anderson, R., & Daugman, J.
- Venue
- IEEE Transactions on Computers
- Published
- 2006-09
- Volume
- 55
- Issue
- 9
- Pages
- 1081-1088
- ISSN
- 0018-9340 (ISSN-L)
- 1557-9956
- 2326-3814
- OpenAlex
- W2165831888
- Cited by
- 600
- References
- 16
- FWCI
- 50.97
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Combining Crypto with Biometrics Effectively. https://app.cochat.ai/papers/10.1109/tc.2006.138
- The paper
- Hao, F., Anderson, R., & Daugman, J. (2006). Combining Crypto with Biometrics Effectively. IEEE Transactions on Computers. https://doi.org/10.1109/tc.2006.138
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.