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Advancement in technology has increased the need to provide adequate security. Hence came the first security system using passwords, these systems have evolved and started using biometrics traits instead of passwords. But people have found ways to cheat such systems through different means. There have been many methods to prevent this security vulnerability, but these methods are very complex or not easy to implement. The most commonly used biometric trait for verification and also the most spoofed biometric trait is fingerprint. The need is to find an easy way to detect a fake fingerprint. The proposed system uses fingerprint and the photo of the fingernail when light is passed through is taken. The image of the fingernail is processed and features are extracted using SIFT and compared with feature vector stored in the database. The correlation is then calculated. Based on the correlation the system decides whether the fingerprint is fake or not. The system was found to react positively to intensity changes in the fingernail image and difference in the pattern of the fingernail. This system provides a simple and robust method for detection of fingerprint spoofing. [ABSTRACT FROM AUTHOR]

Current era is the mobile era and nearly almost every person is having a cell phone and if we say that, cell phone count is more than number of human beings, then it wouldn’t be considered as exaggeration. Technology has started to ruin human life at certain extent. It has also started making impact on them. Like every coin has a two side, technology is helping the human beings to lower down their efforts to achieve the target in optimum time and in some manner, it would also be harmful, if not used either properly or with proper ways by people. So, in this paper, we’ll be focusing on mobile or cellular technology and mobile crimes, mobile crime investigation tools & techniques. [ABSTRACT FROM AUTHOR]

Fingerprint based biometric systems are ubiquitous because they are relatively cheaper to install and maintain, while serving as a fairly accurate biometric trait. However, it has been shown in the past that spoofing attacks on many fingerprint scanners are possible using artificial fingerprints generated using, but not limited to gelatin, Play-Doh and Silicone molds. In this paper, we propose a novel method based on the minutiae count for detecting the fake fingerprints generated using these methods. The proposed algorithm has been tested on the standard FVC (Fingerprint Verification Competition) 2000-2006 dataset and the accuracy was reported to be well above 85%. We also present a literature survey of the previous algorithms for fake fingerprint detection. [ABSTRACT FROM AUTHOR]