Methodology for Evidence Reconstruction in Digital Image Forensics

This paper reveals basics of Digital (Image) Forensics. The paper describes the ways to manipulate image, namely, copy-move forgery (copy region in imag

Methodology for Evidence Reconstruction in Digital Image Forensics

This paper reveals basics of Digital (Image) Forensics. The paper describes the ways to manipulate image, namely, copy-move forgery (copy region in image & paste into another region in same image), image splicing (copy region in image & paste into another image) and image retouching. The paper mainly focuses on copy move forgery detection methods that are classified mainly into two broad approaches- block-based and key-point. Methodology (generalized as well as approach specific) of copy move forgery detection is presented in detail. Copied region is not directly pasted but manipulated (scale, rotation, adding Gaussian noise or combining these transformations) before pasting. The method for detection should robust to these transformations. The paper also presents methodology for reconstruction (if possible) of forged image based on detection result. Keywords: digital forensics, copy-move forgery, keypoint, feature extraction, reconstructio

Enhanced Fuzzy Feature Match Algorithm for Mehndi Fingerprints

The performance of biometric system is degraded by the distortions occurred in finger print image acquisition. This paper focuses on nonlinear distortions occurred due to �Mehndi / Heena drawn on the palm/fingers. The present invention is to detect and rectify such distortions using feedback paradigm. If image is of good quality, there is no need to renovate features. So, quality of whole image is checked by generating exponential similarity distribution. Quality of local region is checked by the ridge continuity map and ridge clarity map. Then, we check whether feedback is needed or not. The desired features such as ridge structure, minutiae point, orientation, etc. are renovated using feedback paradigm. Feedback is taken from top K matched template fingerprints registered in the database. Fuzzy logic handles uncertainties and imperfections in images. For matching, we have proposed the Enhanced Fuzzy Feature Match (EFFM) for estimating triangular feature set of distance between minutiae, orientation angle of minutiae, angle between the direction of minutiae points, angle between the interior bisector of triangle and the direction of minutiae, and a minutiae type. The proposed algorithm incorporates an additional parameter minutiae type that assists to improve accuracy of matching algorithm. The experimentation on 300 Mehndi fingerprints acquired using Secugen fingerprint scanner is conducted. The results positively support EEFM for its efficiency and reliability to handle distorted fingerprints matching

Protection of privacy in biometric data

Biometrics is commonly used in many automated veri cation systems offering several advantages over traditional veri cation methods. Since biometric features are associated with individuals, their leakage will violate individuals\u27 privacy, which can cause serious and continued problems as the biometric data from a person are irreplaceable. To protect the biometric data containing privacy information, a number of privacy-preserving biometric schemes (PPBSs) have been developed over the last decade, but they have various drawbacks. The aim of this paper is to provide a comprehensive overview of the existing PPBSs and give guidance for future privacy-preserving biometric research. In particular, we explain the functional mechanisms of popular PPBSs and present the state-of-the-art privacy-preserving biometric methods based on these mechanisms. Furthermore, we discuss the drawbacks of the existing PPBSs and point out the challenges and future research directions in PPBSs

Validating digital forensic evidence

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This dissertation focuses on the forensic validation of computer evidence. It is a burgeoning field, by necessity, and there have been significant advances in the detection and gathering of evidence related to electronic crimes. What makes the computer forensics field similar to other forensic fields is that considerable emphasis is placed on the validity of the digital evidence. It is not just the methods used to collect the evidence that is a concern. What is also a problem is that perpetrators of digital crimes may be engaged in what is called anti-forensics. Digital forensic evidence techniques are deliberately thwarted and corrupted by those under investigation. In traditional forensics the link between evidence and perpetrator's actions is often straightforward: a fingerprint on an object indicates that someone has touched the object. Anti-forensic activity would be the equivalent of having the ability to change the nature of the fingerprint before, or during the investigation, thus making the forensic evidence collected invalid or less reliable. This thesis reviews the existing security models and digital forensics, paying particular attention to anti-forensic activity that affects the validity of data collected in the form of digital evidence. This thesis will build on the current models in this field and suggest a tentative first step model to manage and detect possibility of anti-forensic activity. The model is concerned with stopping anti-forensic activity, and thus is not a forensic model in the normal sense, it is what will be called a “meta-forensic” model. A meta-forensic approach is an approach intended to stop attempts to invalidate digital forensic evidence. This thesis proposes a formal procedure and guides forensic examiners to look at evidence in a meta-forensic way

A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification

This paper represents the first survey on the application of AI techniques for the analysis of biomedical images with forensic human identification purposes. Human identification is of great relevance in today’s society and, in particular, in medico-legal contexts. As consequence, all technological advances that are introduced in this field can contribute to the increasing necessity for accurate and robust tools that allow for establishing and verifying human identity. We first describe the importance and applicability of forensic anthropology in many identification scenarios. Later, we present the main trends related to the application of computer vision, machine learning and soft computing techniques to the estimation of the biological profile, the identification through comparative radiography and craniofacial superimposition, traumatism and pathology analysis, as well as facial reconstruction. The potentialities and limitations of the employed approaches are described, and we conclude with a discussion about methodological issues and future research.Spanish Ministry of Science, Innovation and UniversitiesEuropean Union (EU) PGC2018-101216-B-I00Regional Government of Andalusia under grant EXAISFI P18-FR-4262Instituto de Salud Carlos IIIEuropean Union (EU) DTS18/00136European Commission H2020-MSCA-IF-2016 through the Skeleton-ID Marie Curie Individual Fellowship 746592Spanish Ministry of Science, Innovation and Universities-CDTI, Neotec program 2019 EXP-00122609/SNEO-20191236European Union (EU)Xunta de Galicia ED431G 2019/01European Union (EU) RTI2018-095894-B-I0