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Front Matter Volume 9409

2015 Media Watermarking, Security, and Forensics 2015  
SPIE uses a six-digit CID article numbering system in which:  The first four digits correspond to the SPIE volume number.  The last two digits indicate publication order within the volume using a Base  ...  The papers published in these proceedings reflect the work and thoughts of the authors and are published herein as submitted.  ...  Contents Recent advances in counter PRNU based source attribution and beyond [9409-29] Mobile visual object identification: from SIFT-BoF-RANSAC to SketchPrint [9409-20] 9409 0R Analysis of optically variable  ... 
doi:10.1117/12.2192149 fatcat:bzwxe5okhrddtazhzdmlgsq33m

Linear Filter Kernel Estimation Based on Digital Camera Sensor Noise

Chang Liu, Matthias Kirchner
2017 IS&T International Symposium on Electronic Imaging Science and Technology  
We study linear filter kernel estimation from processed digital images under the assumption that the image's source camera is known.  ...  The result is a simple yet accurate filter kernel estimation technique that is relatively independent of image content and that does not rely on hand-crafted parameter settings.  ...  Recent advances in data-driven techniques advocate the idea of general-purpose image forensics, where mostly very high-dimensional feature spaces are chosen to detect, identify, or localize a variety of  ... 
doi:10.2352/issn.2470-1173.2017.7.mwsf-332 fatcat:pa3mzu7tojedvjtsu2esmjkxzi

Multimedia Forensics Before the Deep Learning Era [chapter]

Davide Cozzolino, Luisa Verdoliva
2022 Advances in Computer Vision and Pattern Recognition  
We will also briefly review the most interesting features of machine learning- based methods and finally present the major challenges in this area.  ...  The most popular approaches look for artifacts related to the in-camera processing chain (camera-based clues) or the out-camera processing history (editing-based clues).  ...  Acknowledgements This material is based on research sponsored by the Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL) under agreement number FA8750-20-2-1004  ... 
doi:10.1007/978-3-030-87664-7_3 fatcat:zj25humyyzbqxa6qntz25wvvse

Media Forensics and DeepFakes: an overview [article]

Luisa Verdoliva
2020 arXiv   pre-print
With the rapid progress of recent years, techniques that generate and manipulate multimedia content can now guarantee a very advanced level of realism.  ...  On the one hand, this opens the door to a series of exciting applications in different fields such as creative arts, advertising, film production, video games.  ...  Beyond faces, some recent work addressed motion transfer: the target person dances following the movements transferred from a source dancer [46] .  ... 
arXiv:2001.06564v1 fatcat:b3izh3hcmrae5frbd2bv3tmlgu

Information Forensics: An Overview of the First Decade

Matthew C. Stamm, Min Wu, K. J. Ray Liu
2013 IEEE Access  
In recent decades, we have witnessed the evolution of information technologies from the development of VLSI technologies, to communication and networking infrastructure, to the standardization of multimedia  ...  When security is compromised, intellectual rights are violated, or authenticity is forged, forensic methodologies and tools are employed to reconstruct what has happened to digital content in order to  ...  In this section, we discuss advances in ''extrinsic'' fingerprints in the most recent decade.  ... 
doi:10.1109/access.2013.2260814 fatcat:l3hs7vh2nzakpkihwmkubh24dy

Counter-Forensics: Attacking Image Forensics [chapter]

Rainer Böhme, Matthias Kirchner
2012 Digital Image Forensics  
Counter-forensics is first defined in a formal decision-theoretic framework.  ...  Research on counter-forensics is motivated by the need to assess and improve the reliability of forensic methods in situations where intelligent adversaries make efforts to induce a certain outcome of  ...  Acknowledgements Thanks are due to Gang Cao, Thomas Gloe, and Miroslav Goljan for sharing the data of their original research papers.  ... 
doi:10.1007/978-1-4614-0757-7_12 fatcat:amg3sagivbd7ho4fgmg5yehwha

Remote Check Truncation Systems: Vulnerability Analysis and Countermeasures

Hafiz Malik, Rigel Gjomemo, V. N. Venkatakrishnan, Rashid Ansari, Aun Irtaza
2020 IEEE Access  
The proposed countermeasures rely on tamper detection in digital images and expert-system based decision fusion. The effectiveness of the proposed framework is evaluated using tampered check images.  ...  All major banks in the USA and around the world offer remote check deposit services. Consumers can use their smart phones to deposit checks remotely.  ...  methods and recent advances in image manipulation tools provide an attacker with the opportunity to manipulate a digital check image at the pixel level.  ... 
doi:10.1109/access.2020.2982620 fatcat:uegjeqbj5bhfronpxu7kjg7ynq

Vision of the unseen

Anderson Rocha, Walter Scheirer, Terrance Boult, Siome Goldenstein
2011 ACM Computing Surveys  
Thus, a different method, flatfielding, is applied to estimate the FPN and the PRNU. FPN is a signal independent additive noise source, while PRNU is a signal dependent multiplicative noise source.  ...  Recently, Chen et al. [2007a] have investigated the PRNU noise signatures proposed in Lukas et al. [2006] to differentiate specific camcorders (e.g., same brand and model).  ... 
doi:10.1145/1978802.1978805 fatcat:fdd6lebl5zcvlk46ose57uuyja

Conditional Adversarial Camera Model Anonymization [article]

Jerone T. A. Andrews, Yidan Zhang, Lewis D. Griffin
2020 arXiv   pre-print
In contrast to previous works, we cast model anonymization as the process of transforming both high and low spatial frequency information.  ...  Quantitative comparisons demonstrate the efficacy of our framework in a restrictive non-interactive black-box setting.  ...  JTAA is supported by the Royal Academy of Engineering (RAEng) and the Office of the Chief Science Adviser for National Security under the UK Intelligence Community Postdoctoral Fellowship Programme.  ... 
arXiv:2002.07798v3 fatcat:u7a7t7i67ndznny4bse6rw4ize

Detection of AI-Generated Synthetic Faces [chapter]

Diego Gragnaniello, Francesco Marra, Luisa Verdoliva
2022 Advances in Computer Vision and Pattern Recognition  
AbstractIn recent years there have been astonishing advances in AI-based synthetic media generation.  ...  Advanced deep learning tools allow one to easily change some specific attributes of a real face or even create brand new identities.  ...  Acknowledgements This material is based on research sponsored by the Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL) under agreement number FA8750-20-2-1004  ... 
doi:10.1007/978-3-030-87664-7_9 fatcat:xgfieyw72jc4rivptsgekhrei4

Countering Malicious DeepFakes: Survey, Battleground, and Horizon [article]

Felix Juefei-Xu and Run Wang and Yihao Huang and Qing Guo and Lei Ma and Yang Liu
2022 arXiv   pre-print
Nevertheless, the overview of such battleground and the new direction is unclear and neglected by recent surveys due to the rapid increase of related publications, limiting the in-depth understanding of  ...  , e.g., visual effect assistance in movie and misinformation generation by faking famous persons.  ...  among various research groups in order to advance the effort of countering malicious DeepFakes.  ... 
arXiv:2103.00218v3 fatcat:ufeslcp23rghhmx474u25acoje

A Full-Image Full-Resolution End-to-End-Trainable CNN Framework for Image Forgery Detection [article]

Francesco Marra, Diego Gragnaniello, Luisa Verdoliva, Giovanni Poggi
2019 arXiv   pre-print
In this work, we propose a CNN-based image forgery detection framework which makes decisions based on full-resolution information gathered from the whole image.  ...  Due to limited computational and memory resources, current deep learning models accept only rather small images in input, calling for preliminary image resizing.  ...  In recent years, methods based on deep learning have become dominant.  ... 
arXiv:1909.06751v1 fatcat:vwh75pn6ofac5dcf3oy742team

SpoC: Spoofing Camera Fingerprints [article]

Davide Cozzolino and Justus Thies and Andreas Rössler and Matthias Nießner and Luisa Verdoliva
2021 arXiv   pre-print
This is an important study in order to build better forgery detectors able to face malicious attacks. Our proposal consists of a GAN-based approach that injects camera traces into synthetic images.  ...  Given a GAN-generated image, we insert the traces of a specific camera model into it and deceive state-of-the-art detectors into believing the image was acquired by that model.  ...  Such differences help attribute images to their source camera, but can also be used to better highlight anomalies caused by image manipulations [18, 1] .  ... 
arXiv:1911.12069v2 fatcat:oxpy4n63jjgtlp2rayb6tg6fmy

Media Forensics Using Machine Learning Approaches

David Güera
2019
We also propose a set of forensics and counter-forensic techniques to determine the integrity of this multimedia content and modify it in specific ways to deceive adversaries.  ...  In this thesis, we present tools to be able to extract knowledge from and understand this imagery and its provenance.  ...  An up-to-date survey of the last counter-forensics advances can be found in [102] .  ... 
doi:10.25394/pgs.10029749 fatcat:75t5y4z2krhmrfb4xweakaiybe

Towards a demonstrator for autonomous object detection on board Gaia

Shan Mignot, Jacobus M. Oschmann, Jr., Mark C. Clampin, Howard A. MacEwen
2010 Space Telescopes and Instrumentation 2010: Optical, Infrared, and Millimeter Wave  
When PRNU or DSNU significantly affect the reliability of the values read, the column is declared "dead" and the information is considered beyond recovery. 4. Non linearity.  ...  Variability with colour, beyond random effects, can be attributed to the fact that the correspondence between V and G magnitudes also depends on the V − I colour index (because of the dependency of the  ...  The segmentation also corresponds to subdividing the previous operations in pixel-based and object-based domains.  ... 
doi:10.1117/12.857118 fatcat:5z6jahmhszec3bgsvnmapxudym
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