Nowadays, biometrics-based authentication is playing a potential approach for many modern applications such as banking, homeland security etc. However, the end-users may feel uncomfortable to deploy this technology because of not well-solved accurate rate and security problems. To overcome these issues, some significant techniques have been proposed such as biometric template protection, reducing biometric extraction noise etc. Fuzzy vault is one of the most popular methods for biometric template security, which binds a secret key with biometric features and produces one kind of data, called the helper data, for recovering the secret key. Unfortunately, the major drawback of this approach is the lacking of cancellable property. Furthermore, most of the fuzzy vault schemes are performed on two biometrics modalities: fingerprints and iris. Some techniques were introduced to transform the original biometric feature to cancellable one. However, the computational cost of these proposals was quite large. In this research, the authors introduce a periodic transformation attached to fuzzy vault to produce the new cancellable scheme. Their transformation is not only simpler but also suitable for many kinds of biometrics modalities. The experiments demonstrate that this approach is practical with a little better error rate in comparison with the original biometric feature.
['Tran Khanh Dang', 'Quynh Chi Truong', 'Thu Thi Bao Le', 'Hai Truong']
Cancellable fuzzy vault with periodic transformation for biometric template protection