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A Forensic Analysis of the CASIA-Iris V 4 Database

The photo response non-uniformity (PRNU) of a digital image sensor can be useful to enhance a biometric systems security by ensuring the authenticity and integrity of the images acquired with the biometric sensor, i.e. by identifying the image source or detecting a possible tampering of the images presented to the biometric system. Passive image forensic techniques have shown to be suited for this tasks for digital consumer cameras. Previous studies regarding the feasibility of this application using biometric sensors have been conducted for iris and fingerprint sensors by studying the differentiability of the sensors PRNU fingerprints. The results obtained on the CASIA-Iris V4 database showed a high variation among the various subsets of the database. The researchers assumed that this high variation could either be caused by the highly correlated data or come from the usage of different sensors for the acquisition of the subsets. To investigate the latter issue a forensic investigation on the CASIA-Iris V4 database has been performed in this thesis, where an existing forensic technique has been applied and additionally several novel forensic techniques have been proposed to detect the presence of images from multiple sensors in the image data sets. Furthermore, the forensic techniques have been applied on a test data set with a known number of sensors first to evaluate their performance. Since there is no specific documentation on the number of sensors used for the acquisition, the investigation on the CASIA-Iris V4 database has been conducted in a blind manner and without any a priori knowledge about the sensors. In addition different PRNU enhancement approaches have been applied for the investigation to reduce the contamination of the PRNU fingerprints by the image content, which is an issue in this scenario due to the strong correlation of the content among all images under investigation.