Name
Abstract | ||
|---|---|---|
Privacy protection techniques are an important supplementary of biometric systems. Their main purpose is to prevent security leakages in common biometric systems and to preserve the user's privacy. However, when cryptographic functions are used in the algorithms, randomness of biometric features is strictly required from the security point of view. This randomness is hard to achieve in many feature extraction algorithms, especially for those using the local information of biometric modality. In this paper we discuss privacy protection based on a fuzzy extractor. We show that the security of the algorithm is strongly reduced when statistical properties of biometric features as well as the details of the algorithm are known. An attack exploiting feature correlation is demonstrated. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IIH-MSP.2009.237 | IIH-MSP |
Keywords | Field | DocType |
biometric feature,biometric modality,biometric privacy protection schemes,privacy protection,feature extraction algorithm,common biometric system,biometric system,security leakage,feature correlation attack,feature correlation,security point,privacy protection technique,data mining,fuzzy set theory,cryptography,correlation,privacy,security,statistical analysis,iris,feature extraction,data privacy | Data mining,Feature correlation,Feature extraction algorithm,Cryptography,Computer science,Computer security,Feature extraction,Fuzzy set,Biometrics,Information privacy,Randomness | Conference |
Citations | PageRank | References |
7 | 0.47 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuebing Zhou | 1 | 150 | 13.14 |
| Stephen D. Wolthusen | 2 | 301 | 55.45 |
| Christoph Busch | 3 | 339 | 31.75 |
| Arjan Kuijper | 4 | 1063 | 133.22 |