Visible to the public A Policy Framework for Data Fusion and Derived Data Control

TitleA Policy Framework for Data Fusion and Derived Data Control
Publication TypeConference Paper
Year of Publication2016
Authorsden Hartog, Jerry, Zannone, Nicola
Conference NameProceedings of the 2016 ACM International Workshop on Attribute Based Access Control
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4079-3
KeywordsAccess Control, Collaboration, cybersecurity, data fusion, E-Government, Electronic government, Government, Human Behavior, policy, pubcrawl, Resiliency, usage control
Abstract

Recent years have seen an exponential growth of the collection and processing of data from heterogeneous sources for a variety of purposes. Several methods and techniques have been proposed to transform and fuse data into "useful" information. However, the security aspects concerning the fusion of sensitive data are often overlooked. This paper investigates the problem of data fusion and derived data control. In particular, we identify the requirements for regulating the fusion process and eliciting restrictions on the access and usage of derived data. Based on these requirements, we propose an attribute-based policy framework to control the fusion of data from different information sources and under the control of different authorities. The framework comprises two types of policies: access control policies, which define the authorizations governing the resources used in the fusion process, and fusion policies, which define constraints on allowed fusion processes. We also discuss how such policies can be obtained for derived data.

URLhttp://doi.acm.org/10.1145/2875491.2875492
DOI10.1145/2875491.2875492
Citation Keyden_hartog_policy_2016