The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Cancelable Biometrics Realization With Multispace Random Projections
Abstract
Biometric characteristics cannot be changed; therefore, the loss of privacy is permanent if they are ever compromised. This paper presents a two-factor cancelable formulation, where the biometric data are distorted in a revocable but non-reversible manner by first transforming the raw biometric data into a fixed-length feature vector and then projecting the feature vector onto a sequence of random subspaces that were derived from a user-specific pseudorandom number (PRN). This process is revocable and makes replacing biometrics as easy as replacing PRNs. The formulation has been verified under a number of scenarios (normal, stolen PRN, and compromised biometrics scenarios) using 2400 Facial Recognition Technology face images. The diversity property is also examined.
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
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Cited by
Cancelable Biometrics: A review
Patel, V. M., Ratha, N. K., & Chellappa, R. (2015) · IEEE Signal Processing Magazine · doi:10.1109/msp.2015.2434151 · Cited by 419
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
Metadata
- Authors
- Teoh, A. B. J., & Yuang, C. T.
- Venue
- IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)
- Published
- 2007-10
- Volume
- 37
- Issue
- 5
- Pages
- 1096-1106
- ISSN
- 1083-4419 (ISSN-L)
- OpenAlex
- W2103919449
- Cited by
- 183
- References
- 1
- FWCI
- 12.29
- Type
- journal article
- Language
- en
- Open access
- closed
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: Cancelable Biometrics Realization With Multispace Random Projections. https://app.cochat.ai/papers/10.1109/tsmcb.2007.903538
- The paper
- Teoh, A. B. J., & Yuang, C. T. (2007). Cancelable Biometrics Realization With Multispace Random Projections. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics). https://doi.org/10.1109/tsmcb.2007.903538
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.
