150,073 research outputs found

    Securing identity information with image watermarks

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    In this paper, we describe the requirements for embedding watermarks in images used for identity verification and demonstrate a proof of concept in security sciences. The watermarking application is designed for verifying the rightful ownership of a driving license or similar identity object. The tool we built and tested embeds and extracts watermarks that contain verification information of the rightful owner. We used the human finger print of the rightful owner as the watermark. Such information protection mechanisms add an extra layer of security to the information system and improve verification of identification attributes by providing strong security. The issues of usability and cost are also discussed in the context of the social acceptability of access controls

    Identity Meanings and Online Interactions of Hybrid Transnational Communities of Immigants

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    This paper investigates identity in Hybrid Transnational Communities of Immigrants. As predicted by the integrated theory of identity, members enact different salient identities based on situational factors. Community members do enact their placebased identity. However, their role-based identities in the physically community are also brought over to the virtual community. The connection of the virtual community to a geographic location provides members with a tool to verify the identity of others. Members ask or disclose information that can only be known to locals providing a natural filter to screen insiders from outsiders. Members deny their support to any mechanisms to verify the identity of people participating. Even if such mechanisms were enforced, the identity verification is limited because virtual communities have no power, authority or means to verify the identity disclosed

    A Fingerprint Identification Approach using Neural Networks

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    Today, because of the vulnerability of standard authentication system, law-breaking has accumulated within the past few years. Identity authentication that relies on biometric feature like face, iris, voice, hand pure mathematics, handwriting, retina, fingerprints will considerably decrease the fraud, so that they square measure being replaced by identity verification mechanisms. Among bioscience, fingerprint systems are one amongst most generally researched and used. it\'s fashionable due to their easy accessibility. Moreover in this work the system modified to an adaptive system i.e intelligent by using neural networks

    Deploying Virtual Machines on Shared Platforms

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    In this report, we describe mechanisms for secure deployment of virtual machines on shared platforms looking into a telecommunication cloud use case, which is also presented in this report. The architecture we present focuses on the security requirements of the major stakeholders’ part of the scenario we present. This report comprehensively covers all major security aspects including different security mechanisms and protocols, leveraging existing standards and state-of-the art wherever applicable. In particular, our architecture uses TCG technologies for trust establishment in the deployment of operator virtual machines on shared resource platforms. We also propose a novel procedure for securely launching and cryptographically binding a virtual machine to a target platform thereby protecting the operator virtual machine and its related credentials

    Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking

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    This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications
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