Multimedia Security Spoofing of Digital Image Forensics -3d Face Mask

Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or “spoofed”).The recent advances in spoofing detection, current solutions often rely on S domain knowledge, specific biometric reading systems, and attack types. We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face and fingerprint modalities. Multimedia Security spoofing is the act of masquerading as a valid user by falsifying data to gain an illegitimate access. Identification of the spoofing performance of the Tampered or Modified Images 2D Data, Video Images, 3D Face Mask and Morphed Location is proposed. The spoofing performance is further analyzed using Opposite Colour Local Binary Pattern (OCLBP) texture based counter measures using 2D data and is further classified using Support Vector Machine (SVM) classifier.