A model of information flow control to determine whether malfunctions cause the privacy invasion

MPM '12 Pub Date : 2012-04-10 DOI:10.1145/2181196.2181198
David Evans, D. Eyers, J. Bacon
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引用次数: 3

Abstract

Privacy is difficult to assure in complex systems that collect, process, and store data about individuals. The problem is particularly acute when data arise from sensing physical phenomena as individuals are unlikely to realise that actions such as walking past a building generate privacy-sensitive data. Information Flow Control (IFC) is a mature technique for managing security and privacy concerns in large distributed systems. This paper describes (i) how the meta-data required by IFC, in the form of tags, can reflect the physical properties of sensors; and (ii) how the formal expression of the IFC this allows can be used to, statically, determine the proportion of the system that handles private data and how this changes in the face of software or human malfunctions.
一个信息流控制模型,用于确定故障是否导致隐私侵犯
在收集、处理和存储个人数据的复杂系统中,隐私很难得到保证。当数据来自感知物理现象时,这个问题尤其严重,因为个人不太可能意识到,走过一栋建筑等行为会产生隐私敏感数据。信息流控制(IFC)是一种成熟的技术,用于管理大型分布式系统中的安全和隐私问题。本文描述了(i) IFC要求的元数据如何以标签的形式反映传感器的物理特性;以及(ii)如何使用IFC的正式表达式来静态地确定处理私人数据的系统比例,以及面对软件或人为故障时该比例如何变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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