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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,智能家庭,事物互联网和机器学习的全球扩散的大规模变化需要关于机密信息的流程和分类的新颖视野。组织的安全受其成员享有的隐私的影响。这些成员上的足够数据可以在所谓的绑架攻击中利用,旨在从组织中提取机密信息。本文的目的是促进对这种效果的认识。为了说明它,我们开发了一个演员和数据流模型,并讨论了三种情景,其中组织可实现的机密性受到其成员的隐私的限制。

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