A Feature-Based Forensic Procedure for Splicing Forgeries Detection

Nowadays, determining if an image appeared somewhere on the web or in a magazine or is authentic or not has become crucial. Image forensics methods based on features have demonstrated so far to be very effective in detecting forgeries in which a portion of an image is cloned somewhere else onto the same image. Anyway such techniques cannot be adopted to deal with splicing attack, that is, when the image portion comes from another picture that then, usually, is not available anymore for an operation of feature match. In this paper, a procedure in which these techniques could also be employed will be shown to get rid of splicing attack by resorting to the use of some repositories of images available on the Internet like Google Images or TinEye Reverse Image Search. Experimental results are presented on some real case images retrieved on the Internet to demonstrate the capacity of the proposed procedure

Image Origin Classification Based on Social Network Provenance

Recognizing information about the origin of a digital image has been individuated as a crucial task to be tackled by the image forensic scientific community. Understanding something on the previous history of an image could be strategic to address any successive assessment to be made on it: knowing the kind of device used for acquisition or, better, the model of the camera could focus investigations in a specific direction. Sometimes just revealing that a determined post-processing, such as an interpolation or a filtering, has been performed on an image could be of fundamental importance to go back to its provenance. This paper locates in such a context and proposes an innovative method to inquire if an image derives from a social network and, in particular, try to distinguish from, which one has been downloaded. The technique is based on the assumption that each social network applies a peculiar and mostly unknown manipulation that, however, leaves some distinctive traces on the image; such traces can be extracted to feature every platform. By resorting at trained classifiers, the presented methodology is satisfactorily able to discern different social network origins. Experimental results carried out on diverse image datasets and in various operative conditions witness that such a distinction is possible. In addition, the proposed method is also able to go back to the original JPEG quality factor the image had before being uploaded on a social network. © 2005-2012 IEEE

Acquisition source identification through a blind image classification

Image forensics, besides understanding if a digital image has been forged, often aims at determining information about image origin. In particular, it could be worthy to individuate which is the kind of source (digital camera, scanner or computer graphics software) that has generated a certain photo. Such an issue has already been studied in literature, but the problem of doing that in a blind manner has not been faced so far. It is easy to understand that in many application scenarios information at disposal is usually very limited; this is the case when, given a set of L images, the authors want to establish if they belong to K different classes of acquisition sources, without having any previous knowledge about the number of specific types of generation processes. The proposed system is able, in an unsupervised and fast manner, to blindly classify a group of photos without neither any initial information about their membership nor by resorting at a trained classifier. Experimental results have been carried out to verify actual performances of the proposed methodology and a comparative analysis with two SVM-based clustering techniques has been performed too

Smartphone Fingerprinting Combining Features of On-Board Sensors

Many everyday activities involve the exchange of confidential information through the use of a smartphone in mobility, i.e., sending on e-mail, checking bank account, buying on-line, accessing cloud platforms, and health monitoring. This demonstrates how security issues related to these operations are a major challenge in our society and in particular in the cyber-security domain. This paper focuses on the use of the smartphone intrinsic and physical characteristics as a mean to build a smartphone fingerprint to enable devices identification. The basic idea proposed in this paper is to investigate how to generate a specific fingerprint that allows to distinctively and reliably characterize each smartphone. In particular, the accelerometer, the gyroscope, the magnetometer, and the audio system (microphone-speaker) are taken into account to build up a composite fingerprint based on a set of their distinctive features. Many experiments have been carried out by analyzing different classification methods, diverse features combination configurations, and operative scenarios. Satisfactory results have been obtained showing that the combination of such sensors improves smartphone distinctiveness. © 2017 IEEE

Splicing Forgeries Localization through the Use of First Digit Features

One of the principal problems in image forensics is determining if a particular image is authentic or not and, if manipulated, to localize which parts have been altered. In fact, localization is basic within the process of image examination because it permits to link the modified zone with the corresponding image area and, above all, with the meaning of it. Forensic instruments dealing with copy-move manipulation quite always provides a localization map, but, on the contrary, only a few tools, devised to detect a splicing operation, are able to give information about localization too. In this paper, a method to distinguish and then localize a single and a double JPEG compression in portions of an image through the use of the DCT coefficients first digit features and employing a Support Vector Machine (SVM) classifier is proposed. Experimental results and a comparison with a state-of-the-art technique are provided to witness the performances offered by the proposed method in terms of forgery localizatio

Media trustworthiness verification and event assessment through an integrated framework: a case-study

Nowadays, information is provided through diverse network channels and, above all, its diffusion occurs in an always faster and pervasive manner. Social Media (SM) plays a crucial role in distributing, in an uncontrolled way, news, opinions, media contents and so on, and can basically contribute to spread information that sometimes are untrue and misleading. An integrated assessment of the trustworthiness of the information that is delivered is claimed from different sides: the Secure! project strictly fits in such a context. The project has been studying and developing a service oriented infrastructure which, by resorting at diverse technological tools based on image forensics, source reputation analysis, Twitter message trend analysis, web source retrieval and crawling, and so on, provides an integrated event assessment especially regarding crisis management. The aim of this paper is to present an interesting case-study which demonstrates the potentiality of the developed system to achieve a new integrated knowledge. © 2016, Springer Science+Business Media New York