Alessia De Rosa
University of Florence
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Featured researches published by Alessia De Rosa.
international conference on acoustics, speech, and signal processing | 2011
Tiziano Bianchi; Alessia De Rosa; Alessandro Piva
In this paper, we propose a statistical test to discriminate between original and forged regions in JPEG images, under the hypothesis that the former are doubly compressed while the latter are singly compressed. New probability models for the DCT coefficients of singly and doubly compressed regions are proposed, together with a reliable method for estimating the primary quantization factor in the case of double compression. Based on such models, the probability for each DCT block to be forged is derived. Experimental results demonstrate a better discriminating behavior with respect to previously proposed methods.
electronic imaging | 1999
Mauro Barni; Franco Bartolini; Alessia De Rosa; Alessandro Piva
An evaluation of the number of bits that can be hidden within an image by means of frequency-domain watermarking is given. Watermarking is assumed to consist in the modification of a set of full-frame DCT (DFT) coefficients. The amount of modification each coefficient undergoes is proportional to the magnitude of the coefficient itself, so that an additive- multiplicative embedding rule results. The watermark-channel is modeled by letting the watermark be the signal and the image coefficients the noise introduced by the channel. To derive the capacity of each coefficient, the input (i.e. the watermark) and the output (i.e. the watermarked coefficients) of the channel are quantized, thus leading to a discrete- input, discrete-output model. Capacity is evaluated by computing the channel transition matrix and by maximizing the mutual input/output information. Though the results we obtained do not take into account attacks, they represent a useful indication about the amount of information that can be hidden within a single image.
information hiding | 1999
Alessia De Rosa; Mauro Barni; Franco Bartolini; Vito Cappellini; Alessandro Piva
The problem of optimum watermark recovery in a non additive, non Gaussian framework is addressed. Watermark casting is carried out on the frequency domain according to an additive-multiplicative rule. The structure of the optimum decoder is derived based on statistical decision theory. The Neyman-Pearson criterion is used to minimize the probability of missing the watermark for a given false detection rate. Experimental results highlights the superiority of the novel detector scheme with respect to conventional correlation-based decoding.
Journal of Electronic Imaging | 2002
Mauro Barni; Franco Bartolini; Alessia De Rosa; Alessandro Piva
In the field of image watermarking, research has been mainly focused on gray scale image watermarking; the extension to the color case still represents one of the open issues watermarking researchers are faced with. To solve the problem of the correlation among image color bands, a new approach is proposed here which is based on the exploitation of the de-correlation property of the Karhunen-Loeve transform (KLT). The KLT is applied to the red, green, blue components of the host image, then watermarking is performed independently in the discrete Fourier transform (DFT) do- main of the KL-transformed bands. In order to preserve watermark invisibility, embedding is achieved by modifying the magnitude of mid-frequency DFT coefficients according to an additive- multiplicative rule. In detection, KL de-correlation is exploited to de- sign an optimum watermark decoder. In particular, based on the Neyman-Pearson criterion, the watermark presence is revealed by comparing a likelihood function against a threshold. Experimental results are presented proving the robustness of the algorithm against the most common image manipulations, and its superior performance with respect to techniques based on luminance watermarking.
information hiding | 2013
Tiziano Bianchi; Alessia De Rosa; Marco Fontani; Giovanni Rocciolo; Alessandro Piva
In this paper, a method to detect the presence of double compression in a MP3 audio file is proposed. By exploiting the effect of double compression in the statistical properties of quantized MDCT coefficients, a single measure is derived to decide if a MP3 file is single compressed or it has been double compressed and also to devise the bit-rate of the first compression. Experimental results confirm the performance of the detector, mainly when the bit-rate of the second compression is higher than the bit-rate of the first one.
IEEE Signal Processing Letters | 2015
Alessia De Rosa; Marco Fontani; Matteo Massai; Alessandro Piva; Mauro Barni
Image forensic analysis for the detection of contrast enhancement and other histogram-based processing, usually relies on the study of first-order statistics derived from image histogram. Methods based on such an approach, though, are easily circumvented by adopting some counter-forensic attacks. To overcome such a problem, we propose a novel forensic technique based on the study of second-order statistics derived from the co-occurrence matrix. The experiments we carried out demonstrate that the proposed approach is very effective even in the presence of counter-forensic attacks, while it retains the good performance of histogram-based methods when no attack is present.
Handbook of Research on Computational Forensics, Digital Crime, and Investigation | 2010
Roberto Caldelli; Irene Amerini; Francesco Picchioni; Alessia De Rosa; Francesca Uccheddu
Multimedia forensics can be defined as the science that tries, by only analysing a particular digital asset, to give an assessment on such a content and to extract information that can be useful to address and support an investigation linked to the scene represented in that specific digital document. The basic idea behind multimedia forensics relies on the observation that both the acquisition process and any post-processing operation leave a distinctive imprint on the data, as a sort of digital fingerprint. The analysis of such a fingerprint may permit to determine image/video origin and to establish digital content authenticity. DOI: 10.4018/978-1-60566-836-9.ch006
Eurasip Journal on Information Security | 2014
Tiziano Bianchi; Alessia De Rosa; Marco Fontani; Giovanni Rocciolo; Alessandro Piva
In this work, by exploiting the traces left by double compression in the statistics of quantized modified discrete cosine transform coefficients, a single measure has been derived that allows to decide whether an MP3 file is singly or doubly compressed and, in the last case, to devise also the bit-rate of the first compression. Moreover, the proposed method as well as two state-of-the-art methods have been applied to analyze short temporal windows of the track, allowing the localization of possible tampered portions in the MP3 file under analysis. Experiments confirm the good performance of the proposed scheme and demonstrate that current detection methods are useful for tampering localization, thus offering a new tool for the forensic analysis of MP3 audio tracks.
IEEE Transactions on Information Forensics and Security | 2016
Alberto A. de Oliveira; Pasquale Ferrara; Alessia De Rosa; Alessandro Piva; Mauro Barni; Siome Goldenstein; Zanoni Dias; Anderson Rocha
Recently, several studies have been concerned with modeling the parenthood relationships between near duplicates in a set of images. Two images share a parenthood relationship if one is obtained by applying transformations to the other. However, this is not the only form of parenting that can exist among images. An image might be a composition created through the combination of the semantic information existent in two or more source images, establishing a relationship between the sources and the composite. The problem of identifying these relations in a set containing near-duplicate subsets of source and composition images is referred to as multiple parenting phylogeny. Thus far, researchers tackled this problem with a three-step solution: 1) separation of near-duplicate groups; 2) classification of the relations between the groups; and 3) identification of the images used to create the original composition. In this work, we extend upon this framework by introducing key improvements, such as better identification of when two images share content, and improved ways to compare this content. In addition, we also introduce a new realistic professionally created data set of compositions involving multiple parenting relationships. The method we present in this paper is properly evaluated through quantitative metrics, established for assessing the accuracy in finding multiple parenting relationships. Finally, we discuss some particularities of the framework, such as the importance of an accurate reconstruction of phylogenies and the methods behavior when dealing with more complex compositions.
acm workshop on multimedia and security | 2010
Marco Fontani; Alessia De Rosa; Roberto Caldelli; Francesco Filippini; Alessandro Piva; Matteo Consalvo; Vito Cappellini
Reversible digital watermarking has been indicated as the technology to be adopted when image security is to be granted in a medical application scenario. The work presented hereafter provides a new lossless watermarking algorithm designed to really be integrated in a Picture Archiving and Communication System matching the requirements coming from radiological experts. The proposed technique has been developed by modifying and improving the methodology implemented in [3]. Experimental results carried out on medical imagery are provided to demonstrate performance enhancement.