192,573 research outputs found

    e-Counterfeit: a mobile-server platform for document counterfeit detection

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    This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that is usually printed in documents as IDs or banknotes. The main contribution of this work is the end-to-end mobile-server architecture, which provides a service for non-expert users and therefore can be used in several scenarios. The system also provides a crowdsourcing mode so labeled images can be gathered, generating databases for incremental training of the algorithms.Comment: 6 pages, 5 figure

    On the Use of XML in Medical Imaging Web-Based Applications

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    The rapid growth of digital technology in medical fields over recent years has increased the need for applications able to manage patient medical records, imaging data, and chart information. Web-based applications are implemented with the purpose to link digital databases, storage and transmission protocols, management of large volumes of data and security concepts, allowing the possibility to read, analyze, and even diagnose remotely from the medical center where the information was acquired. The objective of this paper is to analyze the use of the Extensible Markup Language (XML) language in web-based applications that aid in diagnosis or treatment of patients, considering how this protocol allows indexing and exchanging the huge amount of information associated with each medical case. The purpose of this paper is to point out the main advantages and drawbacks of the XML technology in order to provide key ideas for future web-based applicationsPeer ReviewedPostprint (author's final draft

    Vulnerable GPU Memory Management: Towards Recovering Raw Data from GPU

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    In this paper, we present that security threats coming with existing GPU memory management strategy are overlooked, which opens a back door for adversaries to freely break the memory isolation: they enable adversaries without any privilege in a computer to recover the raw memory data left by previous processes directly. More importantly, such attacks can work on not only normal multi-user operating systems, but also cloud computing platforms. To demonstrate the seriousness of such attacks, we recovered original data directly from GPU memory residues left by exited commodity applications, including Google Chrome, Adobe Reader, GIMP, Matlab. The results show that, because of the vulnerable memory management strategy, commodity applications in our experiments are all affected

    KAPTUR: technical analysis report

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    Led by the Visual Arts Data Service (VADS) and funded by the JISC Managing Research Data programme (2011-13) KAPTUR will discover, create and pilot a sectoral model of best practice in the management of research data in the visual arts in collaboration with four institutional partners: Glasgow School of Art; Goldsmiths, University of London; University for the Creative Arts; and University of the Arts London. This report is framed around the research question: which technical system is most suitable for managing visual arts research data? The first stage involved a literature review including information gathered through attendance at meetings and events, and Internet research, as well as information on projects from the previous round of JISCMRD funding (2009-11). During February and March 2012, the Technical Manager carried out interviews with the four KAPTUR Project Officers and also met with IT staff at each institution. This led to the creation of a user requirement document (Appendix A), which was then circulated to the project team for additional comments and feedback. The Technical Manager selected 17 systems to compare with the user requirement document (Appendix B). Five of the systems had similar scores so these were short-listed. The Technical Manager created an online form into which the Project Officers entered priority scores for each of the user requirements in order to calculate a more accurate score for each of the five short-listed systems (Appendix C) and this resulted in the choice of EPrints as the software for the KAPTUR project

    Automated Dynamic Firmware Analysis at Scale: A Case Study on Embedded Web Interfaces

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    Embedded devices are becoming more widespread, interconnected, and web-enabled than ever. However, recent studies showed that these devices are far from being secure. Moreover, many embedded systems rely on web interfaces for user interaction or administration. Unfortunately, web security is known to be difficult, and therefore the web interfaces of embedded systems represent a considerable attack surface. In this paper, we present the first fully automated framework that applies dynamic firmware analysis techniques to achieve, in a scalable manner, automated vulnerability discovery within embedded firmware images. We apply our framework to study the security of embedded web interfaces running in Commercial Off-The-Shelf (COTS) embedded devices, such as routers, DSL/cable modems, VoIP phones, IP/CCTV cameras. We introduce a methodology and implement a scalable framework for discovery of vulnerabilities in embedded web interfaces regardless of the vendor, device, or architecture. To achieve this goal, our framework performs full system emulation to achieve the execution of firmware images in a software-only environment, i.e., without involving any physical embedded devices. Then, we analyze the web interfaces within the firmware using both static and dynamic tools. We also present some interesting case-studies, and discuss the main challenges associated with the dynamic analysis of firmware images and their web interfaces and network services. The observations we make in this paper shed light on an important aspect of embedded devices which was not previously studied at a large scale. We validate our framework by testing it on 1925 firmware images from 54 different vendors. We discover important vulnerabilities in 185 firmware images, affecting nearly a quarter of vendors in our dataset. These experimental results demonstrate the effectiveness of our approach
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