Altered Fingerprints: Analysis and Detection

Abstract

Abstract-The widespread deployment of Automated Fingerprint Identification Systems (AFIS) in law enforcement and border control applications has heightened the need for ensuring that these systems are not compromised. While several issues related to fingerprint system security have been investigated, including the use of fake fingerprints for masquerading identity, the problem of fingerprint alteration or obfuscation has received very little attention. Fingerprint obfuscation refers to the deliberate alteration of the fingerprint pattern by an individual for the purpose of masking his identity. Several cases of fingerprint obfuscation have been reported in the press. Fingerprint image quality assessment software (e.g., NFIQ) cannot always detect altered fingerprints since the implicit image quality due to alteration may not change significantly. The main contributions of this paper are: 1) compiling case studies of incidents where individuals were found to have altered their fingerprints for circumventing AFIS, 2) investigating the impact of fingerprint alteration on the accuracy of a commercial fingerprint matcher, 3) classifying the alterations into three major categories and suggesting possible countermeasures, 4) developing a technique to automatically detect altered fingerprints based on analyzing orientation field and minutiae distribution, and 5) evaluating the proposed technique and the NFIQ algorithm on a large database of altered fingerprints provided by a law enforcement agency. Experimental results show the feasibility of the proposed approach in detecting altered fingerprints and highlight the need to further pursue this problem.

Recognizing Disguised Faces: Human and Machine Evaluation

“…It involves both intentional and unintentional changes on a face through which one can either obfuscate his/her identity and/or impersonate someone else's identity. In either case, facial disguise falls under the broader category of biometric obfuscation [22]. Figure 1 shows an example of face obfuscation where the appearance of a subject can vary by using different disguise accessories.…”

A Support Vector Machine Approach for Truncated Fingerprint Image Detection from Sweeping Fingerprint Sensors

“…It can also be observed that the insignificant features of truncated fingerprints may easily disappear after performing image reconstruction and enhancement procedures. Nevertheless, existing detection algorithms [10,11] for fingerprint image analysis always focused on checking the adequate feature number of minutiae/ridges [12,13] or image qualities [14,15,16], and most of algorithms spend a lot of time on determining the validity of a fingerprint [17,18,19]. For example, one of the most reliable fingerprint quality inspection systems is the Fingerprint Image Quality (NFIQ) [20] which was developed and maintained by National Institute of Standard and Technology (NIST) in United States.…”

The Potential of Using Brain Images for Authentication

“…Compared with other biometric techniques, brain recognition is more resistant to forgery (e.g., fake fingerprints [15]) and spoofing (e.g., face disguise [16]). Brain recognition is also more reliable to identify the escapee since one's brain can hardly be modified, whereas other biologic traits may be altered, such as altered fingerprints [17]. Palaniappan and Mandic [18] established a Visual Evoked Potential- (VEP-) based biometrics, and simulations have indicated the significant potential of brain electrical activity as a biometric tool.…”