Do GANs leave artificial fingerprints?

In the last few years, generative adversarial networks (GAN) have shown tremendous potential for a number of applications in computer vision and related fields. With the current pace of progress, it is a sure bet they will soon be able to generate high-quality images and videos, virtually indistinguishable from real ones. Unfortunately, realistic GAN-generated images pose serious threats to security, to begin with a possible flood of fake multimedia, and multimedia forensic countermeasures are in urgent need. In this work, we show that each GAN leaves its specific fingerprint in the images it generates, just like real-world cameras mark acquired images with traces of their photo-response non-uniformity pattern. Source identification experiments with several popular GANs show such fingerprints to represent a precious asset for forensic analyses

Analysis of adversarial attacks against CNN-based image forgery detectors

With the ubiquitous diffusion of social networks, images are becoming a dominant and powerful communication channel. Not surprisingly, they are also increasingly subject to manipulations aimed at distorting information and spreading fake news. In recent years, the scientific community has devoted major efforts to contrast this menace, and many image forgery detectors have been proposed. Currently, due to the success of deep learning in many multimedia processing tasks, there is high interest towards CNN-based detectors, and early results are already very promising. Recent studies in computer vision, however, have shown CNNs to be highly vulnerable to adversarial attacks, small perturbations of the input data which drive the network towards erroneous classification. In this paper we analyze the vulnerability of CNN-based image forensics methods to adversarial attacks, considering several detectors and several types of attack, and testing performance on a wide range of common manipulations, both easily and hardly detectable

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

Due to limited computational and memory resources, current deep learning models accept only rather small images in input, calling for preliminary image resizing. This is not a problem for high-level vision problems, where discriminative features are barely affected by resizing. On the contrary, in image forensics, resizing tends to destroy precious high-frequency details, impacting heavily on performance. One can avoid resizing by means of patch-wise processing, at the cost of renouncing whole-image analysis. 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. Thanks to gradient checkpointing, the framework is trainable end-to-end with limited memory resources and weak (image-level) supervision, allowing for the joint optimization of all parameters. Experiments on widespread image forensics datasets prove the good performance of the proposed approach, which largely outperforms all baselines and all reference methods.Comment: 13 pages, 12 figures, journa

Perceptual Quality-preserving Black-Box Attack against Deep Learning Image Classifiers

Deep neural networks provide unprecedented performance in all image classification problems, taking advantage of huge amounts of data available for training. Recent studies, however, have shown their vulnerability to adversarial attacks, spawning an intense research effort in this field. With the aim of building better systems, new countermeasures and stronger attacks are proposed by the day. On the attacker's side, there is growing interest for the realistic black-box scenario, in which the user has no access to the neural network parameters. The problem is to design efficient attacks which mislead the neural network without compromising image quality. In this work, we propose to perform the black-box attack along a low-distortion path, so as to improve both the attack efficiency and the perceptual quality of the adversarial image. Numerical experiments on real-world systems prove the effectiveness of the proposed approach, both in benchmark classification tasks and in key applications in biometrics and forensics.Comment: 8 pages, journa

Are GAN generated images easy to detect? A critical analysis of the state-of-the-art

The advent of deep learning has brought a significant improvement in the quality of generated media. However, with the increased level of photorealism, synthetic media are becoming hardly distinguishable from real ones, raising serious concerns about the spread of fake or manipulated information over the Internet. In this context, it is important to develop automated tools to reliably and timely detect synthetic media. In this work, we analyze the state-of-the-art methods for the detection of synthetic images, highlighting the key ingredients of the most successful approaches, and comparing their performance over existing generative architectures. We will devote special attention to realistic and challenging scenarios, like media uploaded on social networks or generated by new and unseen architectures, analyzing the impact of suitable augmentation and training strategies on the detectors' generalization ability.Comment: 7 pages, 5 figures, conferenc

Insulin stimulates fibroblast proliferation through calcium-calmodulin-dependent kinase II.

Insulin effects are mediated by multiple integrated signals generated by the insulin receptor. Fibroblasts, as most of mammalian cells, are a target of insulin action and are impor- tant actors in the vascular pathogenesis of hyperinsulinemia. A role for calcium-calmodulin-dependent kinases (CaMK) in insulin signaling has been proposed but has been under inves- tigated. We investigated the role of the CaMK isoform II in insulin signaling in human fibroblasts. A rapid and transient increase of intracellular calcium concentration was induced by insulin stimulation, followed by increase of CaMKII activity, via L type calcium channels. Concomitantly, insulin stimula- tion induced Raf-1 and ERK activation, followed by thymidine uptake. Inhibition of CaMKII abrogated the insulin-induced Raf-1 and ERK activation, resulting also in the inhibition of thymidine incorporation. These results demonstrate that in fibroblasts, insulin-activated CaMKII is necessary, together with Raf-1, for ERK activation and cell proliferation. This represents a novel mechanism in the control of insulin signals leading to fibroblast proliferation, as well as a putative site for pharmacological intervention

Insulin stimulates fibroblast proliferation through calcium-calmodulin-dependent kinase II.

Insulin effects are mediated by multiple integrated signals generated by the insulin receptor. Fibroblasts, as most of mammalian cells, are a target of insulin action and are impor- tant actors in the vascular pathogenesis of hyperinsulinemia. A role for calcium-calmodulin-dependent kinases (CaMK) in insulin signaling has been proposed but has been under inves- tigated. We investigated the role of the CaMK isoform II in insulin signaling in human fibroblasts. A rapid and transient increase of intracellular calcium concentration was induced by insulin stimulation, followed by increase of CaMKII activity, via L type calcium channels. Concomitantly, insulin stimula- tion induced Raf-1 and ERK activation, followed by thymidine uptake. Inhibition of CaMKII abrogated the insulin-induced Raf-1 and ERK activation, resulting also in the inhibition of thymidine incorporation. These results demonstrate that in fibroblasts, insulin-activated CaMKII is necessary, together with Raf-1, for ERK activation and cell proliferation. This represents a novel mechanism in the control of insulin signals leading to fibroblast proliferation, as well as a putative site for pharmacological intervention

Ordered Arrays of Size-Selected Oxide Nanoparticles

A bottom-up approach to produce a long-range ordered superlattice of monodisperse and isomorphic metal-oxide nanoparticles (NP) supported onto an oxide substrate is demonstrated. The synthetic strategy consists of self-assembling metallic NP on an ultrathin nanopatterned aluminum oxide template followed by a morphology-conserving oxidation process, and is exemplified in the case of Ni, but is generally applicable to a wide range of metallic systems. Both fully oxidized and core-shell metal-metal-oxide particles are synthesized, up to 3-4 nm in diameter, and characterized via spectroscopic and theoretical tools. This opens up a new avenue for probing unit and ensemble effects on the properties of oxide materials in the nanoscale regime

Alteration of the Cortical Actin Cytoskeleton Deregulates Ca2+ Signaling, Monospermic Fertilization, and Sperm Entry

Background: When preparing for fertilization, oocytes undergo meiotic maturation during which structural changes occur in the endoplasmic reticulum (ER) that lead to a more efficient calcium response. During meiotic maturation and subsequent fertilization, the actin cytoskeleton also undergoes dramatic restructuring. We have recently observed that rearrangements of the actin cytoskeleton induced by actin-depolymerizing agents, or by actin-binding proteins, strongly modulate intracellular calcium (Ca 2+) signals during the maturation process. However, the significance of the dynamic changes in F-actin within the fertilized egg has been largely unclear. Methodology/Principal Findings: We have measured changes in intracellular Ca 2+ signals and F-actin structures during fertilization. We also report the unexpected observation that the conventional antagonist of the InsP3 receptor, heparin, hyperpolymerizes the cortical actin cytoskeleton in postmeiotic eggs. Using heparin and other pharmacological agents that either hypo- or hyperpolymerize the cortical actin, we demonstrate that nearly all aspects of the fertilization process are profoundly affected by the dynamic restructuring of the egg cortical actin cytoskeleton. Conclusions/Significance: Our findings identify important roles for subplasmalemmal actin fibers in the process of spermegg interaction and in the subsequent events related to fertilization: the generation of Ca 2+ signals, sperm penetration