1,720,969 research outputs found
Image Origin Classification Based on Social Network Provenance
Full text linkRecognizing 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
Splicing Forgeries Localization through the Use of First Digit Features
No full textOne 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
Acquisition source identification through a blind image classification
No full textImage 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
Full text linkMany 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
Media trustworthiness verification and event assessment through an integrated framework: a case-study
No full textNowadays, 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
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Adversarial Examples Detection in Features Distance Spaces
No full textMaliciously manipulated inputs for attacking machine learning methods – in particular deep neural networks – are emerging as a relevant issue for the security of recent artificial intelligence technologies, especially in computer vision. In this paper, we focus on attacks targeting image classifiers implemented with deep neural networks, and we propose a method for detecting adversarial images which focuses on the trajectory of internal representations (i.e. hidden layers neurons activation, also known as deep features) from the very first, up to the last. We argue that the representations of adversarial inputs follow a different evolution with respect to genuine inputs, and we define a distance-based embedding of features to efficiently encode this information. We train an LSTM network that analyzes the sequence of deep features embedded in a distance space to detect adversarial examples. The results of our preliminary experiments are encouraging: our detection scheme is able to detect adversarial inputs targeted to the ResNet-50 classifier pre-trained on the ILSVRC’12 dataset and generated by a variety of crafting algorithms
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