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A new biometric-based security framework for cloud storage

机译:一种新的基于生物特征的云存储安全框架

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Cloud computing is a paradigm that is redrawing the information technology landscape by outsourcing the computation and data storage services to public cloud service providers. Over the last years, cloud storage services revealed an unprecedented opportunity for Internet users to profit from online storage services. Thanks to their enriched toolbox for file sharing and syncing, cloud storage platforms provide organizations and individuals with a reliable and cost-effective collaborative workspace. However, in addition to the traditional security issues, cloud storage services introduce new security concerns that are mainly related to the insecure state in which the files are while being synchronized. Recent publications highlighted the significant impact of the security flaws that exist in the syncing protocols used by the most popular cloud storage application. In this paper, we consider the Man in the Cloud (MitC) attack demonstrated in 2015 which allows accessing the files stored in a private repository without the possession of the authentication and authorization credentials. To address this issue, we propose a biometric-based framework for cloud storage services aiming to impede intruders from launching MitC attacks. Our framework is based on our previously published technique to combine chaotic maps and fuzzy extractors. The experiments performed on real biometric features confirm the potential brought by our framework to implement strong authentication in cloud storage applications.
机译:云计算是通过将计算和数据存储服务外包给公共云服务提供商来重绘信息技术领域的范例。在过去的几年中,云存储服务为互联网用户提供了前所未有的机会,可以从在线存储服务中获利。由于其丰富的文件共享和同步工具箱,云存储平台为组织和个人提供了可靠且经济高效的协作工作区。但是,除了传统的安全性问题之外,云存储服务还引入了新的安全性问题,这些问题主要与文件在同步时处于不安全状态有关。最近的出版物强调了最流行的云存储应用程序使用的同步协议中存在的安全漏洞的重大影响。在本文中,我们考虑了2015年演示的“云端中的人(MitC)”攻击,该攻击允许访问存储在私有存储库中的文件而无需身份验证和授权凭证。为了解决此问题,我们提出了一种基于生物识别技术的云存储服务框架,旨在阻止入侵者发起MitC攻击。我们的框架基于我们先前发布的技术,将混沌映射和模糊提取器结合在一起。对真实生物特征进行的实验证实了我们的框架带来的潜力,可以在云存储应用程序中实施强大的身份验证。

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