58 research outputs found
User-friendly system (A smartphone app) for reporting violent incidents towards emergency nurses in the emergency department: An Italian multicenter study
Optical Systems Identification through Rayleigh Backscattering
: We introduce a technique to generate and read the digital signature of the networks, channels, and optical devices that possess the fiber-optic pigtails to enhance physical layer security (PLS). Attributing a signature to the networks or devices eases the identification and authentication of networks and systems thus reducing their vulnerability to physical and digital attacks. The signatures are generated using an optical physical unclonable function (OPUF). Considering that OPUFs are established as the most potent anti-counterfeiting tool, the created signatures are robust against malicious attacks such as tampering and cyber attacks. We investigate Rayleigh backscattering signal (RBS) as a strong OPUF to generate reliable signatures. Contrary to other OPUFs that must be fabricated, the RBS-based OPUF is an inherent feature of fibers and can be easily obtained using optical frequency domain reflectometry (OFDR). We evaluate the security of the generated signatures in terms of their robustness against prediction and cloning. We demonstrate the robustness of signatures against digital and physical attacks confirming the unpredictability and unclonability features of the generated signatures. We explore signature cyber security by considering the random structure of the produced signatures. To demonstrate signature reproducibility through repeated measurements, we simulate the signature of a system by adding a random Gaussian white noise to the signal. This model is proposed to address services including security, authentication, identification, and monitoring
A novel semi-fragile forensic watermarking scheme for remote sensing images
Peer-reviewedA semi-fragile watermarking scheme for multiple band images is presented. We propose to embed a mark into remote sensing images applying a tree structured vector quantization approach to the pixel signatures, instead of processing each band separately. The signature of themmultispectral or hyperspectral image is used to embed the mark in it order to detect any significant modification of the original image. The image is segmented into threedimensional blocks and a tree structured vector quantizer is built for each block. These trees are manipulated using an iterative algorithm until the resulting block satisfies a required criterion which establishes the embedded mark. The method is shown to be able to preserve the mark under lossy compression (above a given threshold) but, at the same time, it detects possibly forged blocks and their position in the whole image.Se presenta un esquema de marcas de agua semi-frágiles para múltiples imágenes de banda. Proponemos incorporar una marca en imágenes de detección remota, aplicando un enfoque de cuantización del vector de árbol estructurado con las definiciones de píxel, en lugar de procesar cada banda por separado. La firma de la imagen hiperespectral se utiliza para insertar la marca en el mismo orden para detectar cualquier modificación significativa de la imagen original. La imagen es segmentada en bloques tridimensionales y un cuantificador de vector de estructura de árbol se construye para cada bloque. Estos árboles son manipulados utilizando un algoritmo iteractivo hasta que el bloque resultante satisface un criterio necesario que establece la marca incrustada. El método se muestra para poder preservar la marca bajo compresión con pérdida (por encima de un umbral establecido) pero, al mismo tiempo, detecta posiblemente bloques forjados y su posición en la imagen entera.Es presenta un esquema de marques d'aigua semi-fràgils per a múltiples imatges de banda. Proposem incorporar una marca en imatges de detecció remota, aplicant un enfocament de quantització del vector d'arbre estructurat amb les definicions de píxel, en lloc de processar cada banda per separat. La signatura de la imatge hiperespectral s'utilitza per inserir la marca en el mateix ordre per detectar qualsevol modificació significativa de la imatge original. La imatge és segmentada en blocs tridimensionals i un quantificador de vector d'estructura d'arbre es construeix per a cada bloc. Aquests arbres són manipulats utilitzant un algoritme iteractiu fins que el bloc resultant satisfà un criteri necessari que estableix la marca incrustada. El mètode es mostra per poder preservar la marca sota compressió amb pèrdua (per sobre d'un llindar establert) però, al mateix temps, detecta possiblement blocs forjats i la seva posició en la imatge sencera
Provenance analysis for instagram photos
As a feasible device fingerprint, sensor pattern noise (SPN) has been proven to be effective in the provenance analysis of digital images. However, with the rise of social media, millions of images are being uploaded to and shared through social media sites every day. An image downloaded from social networks may have gone through a series of unknown image manipulations. Consequently, the trustworthiness of SPN has been challenged in the provenance analysis of the images downloaded from social media platforms. In this paper, we intend to investigate the effects of the pre-defined Instagram images filters on the SPN-based image provenance analysis. We identify two groups of filters that affect the SPN in quite different ways, with Group I consisting of the filters that severely attenuate the SPN and Group II consisting of the filters that well preserve the SPN in the images. We further propose a CNN-based classifier to perform filter-oriented image categorization, aiming to exclude the images manipulated by the filters in Group I and thus improve the reliability of the SPN-based provenance analysis. The results on about 20, 000 images and 18 filters are very promising, with an accuracy higher than 96% in differentiating the filters in Group I and Group II
Fast source camera identification using matching signs between query and reference fingerprints
La falsificazione epigrafica. Questioni di metodo e casi di studio
This paper aims to reconsider the manuscript by Jacopo Valvasone (1499-1570), formerly owned by the Earl of Leicester (now British Library, Additional MS 49369), which Theodor Mommsen borrowed and inspected in 1876, just before the publication of the second part of CIL V. In the letter that he wrote to thank the Vicar and Librarian of Halkham Hall, Mommsen declared that Valvasone joined \u201cthe the long list of forgers\u201d. The analysis of forgeries in Valvasone\u2019s manuscript could show whether Mommsen was right in his opinion
SIFT match removal and keypoint preservation through dominant orientation shift
In Image Forensics, very often, copy-move attack is countered by resorting at instruments based on matching local features descriptors, usually SIFT. On the other side, to overcome such techniques, smart hackers can try firstly to remove keypoints before performing image patch cloning in order to inhibit the successive matching operation. However, keypoint removal determines per se some suspicious empty areas that could indicate that a manipulation has occurred. In this paper, the goal to nullify SIFT matches while preserving keypoints is pursued. The basic idea is to succeed in altering the features descriptor by means of shifting the dominant orientation associated to a specific keypoint. In fact, to provide rotation invariance, all the values of the descriptor are computed according to such orientation. So doing, it should impair the whole matching phase. © 2015 EURASIP
An analysis on attacker actions in fingerprint-copy attack in source camera identification
Multimedia forensics deals with the analysis of multimedia data to gather information on their origin and authenticity through the use of specific tools. At this point an important question arises: how much reliable are these algorithms? In this work we have considered the technique presented in [1] where it is shown how source camera identification can be attacked. In particular, the problem investigated concerns the situation when an adversary estimates the sensor fingerprint from a set of images belonging to the person he wants to frame and superimposes it onto an image acquired by a different camera to charge the innocent victim as the author of that photo. In [1], a countermeasure against such attack, named Triangle Test, is introduced. In this paper we have analyzed if a more sophisticated action of the attacker can invalidate such countermeasure. Experimental results are provided to prove how hacker's action could be improved
Distinguishing between camera and scanned images by means of frequency analysis
Distinguishing the kind of sensor which has acquired a digital image could be crucial in many scenarios where digital forensic techniques are called to give answers. In this paper a new methodology which
permits to determine if a digital photo has been taken by a camera or
has been scanned by a scanner is proposed. Such a technique exploits
the specific geometrical features of the sensor pattern noise introduced
by the sensor in both cases and by resorting to a frequency analysis can
infer if a periodicity is present and consequently which is the origin of
the digital content. Experimental results are presented to support the
theoretical framework
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