Data provenance to audit compliance with privacy policy in the Internet of Things

被引：35

作者：

Pasquier, Thomas ^{[1
]}

Singh, Jatinder ^{[2
]}

Powles, Julia ^{[3
]}

Eyers, David ^{[4
]}

Seltzer, Margo ^{[1
]}

Bacon, Jean ^{[2
]}

机构：

[1] Harvard Univ, Ctr Res Computat & Soc, Cambridge, MA 02138 USA

[2] Univ Cambridge, Comp Lab, Cambridge, England

[3] Cornell Tech, Comp & Informat Sci, New York, NY USA

[4] Univ Otago, Dept Comp Sci, Dunedin, New Zealand

来源：

PERSONAL AND UBIQUITOUS COMPUTING | 2018年 / 22卷 / 02期

基金：

英国工程与自然科学研究理事会; 美国国家科学基金会;

关键词：

SECURITY; LANGUAGE;

D O I：

10.1007/s00779-017-1067-4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Managing privacy in the IoT presents a significant challenge. We make the case that information obtained by auditing the flows of data can assist in demonstrating that the systems handling personal data satisfy regulatory and user requirements. Thus, components handling personal data should be audited to demonstrate that their actions comply with all such policies and requirements. A valuable side-effect of this approach is that such an auditing process will highlight areas where technical enforcement has been incompletely or incorrectly specified. There is a clear role for technical assistance in aligning privacy policy enforcement mechanisms with data protection regulations. The first step necessary in producing technology to accomplish this alignment is to gather evidence of data flows. We describe our work producing, representing and querying audit data and discuss outstanding challenges.

引用

页码：333 / 344

页数：12

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