Most of the existing techniques for the fingerprint privacy protection make use of a key and which creates the
inconvenience. When both the key and the protected fingerprint are stolen and there may open for attacks. Teoh et
al2 propose a bio-hashing approach, which generates a unique code for a person by combining tokenized random
data with the fingerprint. The accuracy of this two factor authentication approach is depends on the key, which is
assumed to be never stolen or shared. It is vulnerable to intrusion and linkage attacks when both the key and the
transformed template are stolen.
There are only a few schemes that are able to protect the privacy of the fingerprint without using a key. Ross and
Othman 3 propose this approach by using visual cryptography for protecting the privacy of biometrics. The
fingerprint image is decomposed using a visual cryptography scheme to produce two noise-like images (termed as
sheets) which are stored in two separate databases. During the authentication, the two sheets are overlaid to create a
temporary fingerprint image for matching. The advantage of this system is that the identity of the biometrics is never
exposed to the attacker in a single database.
Berrin Yanikoglu et al 4 propose a biometric authentication framework to address the privacy by using two
separate biometric features, combined to obtain a non-unique identifier of the individual. A combined biometric ID
composed of two fingerprints is stored in the central database, and imprints from both fingers are required in the
verification process, reduce the misuse and privacy loss. The concept of combining two different fingerprints into a
new identity is first proposed, where the new identity is created by combining the minutiae positions extracted from
the two fingerprints. The original minutiae positions of each fingerprint can be protected in the new identity.
However, it is easy for the attacker to identify such a new identity because it contains many more minutiae positions
than that of an original fingerprint.
Arun Ross et al 5 propose mixing fingerprints for template security and privacy, to combine two different
fingerprints in the image level. In this work, an input fingerprint image is mixed with another fingerprint, in order to
produce a new mixed image that hides the identity of the original fingerprint. To mix two fingerprints, each
fingerprint is decomposed into continuous and spiral components. After pre-aligning generate a mixed fingerprint by
combining the two components of each fingerprint.
When the user identity is linked with the fingerprint features to add more authentication factors to the
authentication process. If monitoring and owner identification applications place the same watermark in all copies of
the same content, it may create a problem. To solve that problem the user identity is thrashed with the fingerprint
image using watermark approach. A digital watermark algorithm is one of the most researched methods to protect
fingerprint images and there are several characteristics that a good watermark technique it should be perceptually
invisible and resistant to common image processing operations.
Rhoads 6 described a method that adds or subtracts small random quantities from each pixel. By comparing a
binary mask of bits with the LSB of each pixel thus determine the method is added or subtracted. If the LSB is equal
to the corresponding mask bit, then the random quantity is added, otherwise it is subtracted. This method does not
make use of perceptual relevance and provide some robustness to low-pass filtering. This scheme does not consider
the problem of collusion attacks.
Recently 7, 8 proposed a watermarking algorithm for fingerprint image protection without corrupting minutiae
points. This method embeds a watermark into a fingerprint image using the DCT technique. The idea behind this
method is the watermark is embedded into the DCT blocks which contain two minutiae points or less. The template
and the host fingerprint are exactly the same image. The watermark effect is determined by comparing the total
number of minutiae points before and after watermark embedding