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Individual Privacy Supporting Organisational Security

机译:个人隐私支持组织安全

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摘要

The large-scale change emergent from the global proliferation of cloud computing, smart homes, the internet of things and machine learning requires a novel view on the flow of confidential information and its classification. The security of an organisation is affected by the privacy enjoyed by its members. Sufficient data on those members can be leveraged in a so-called abduction attack aiming to extract confidential information from the organisation. The intention of this paper is to foster awareness of this effect. To illustrate it we develop a model of actors and data flows and discuss three scenarios in which he confidentiality achievable by an organisation is limited by the privacy of its members.
机译:云计算,智能家居,物联网和机器学习在全球范围内的激增引起了大规模的变化,这需要对机密信息流及其分类提出一种新颖的看法。组织的安全性受到其成员享有的隐私的影响。可以在所谓的绑架攻击中利用有关这些成员的足够数据,以从组织中提取机密信息。本文的目的是提高人们对此效应的认识。为了说明这一点,我们建立了一个参与者和数据流模型,并讨论了三种情况,在这种情况下,组织可以实现的机密性受到其成员隐私的限制。

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