Barhamgi, Mahmoud, Perera, Charith, Yu, Chia-Mu, Benslimane, Djamal, Camacho, David and Bonnet, Christine
2020.
Privacy in data service composition.
IEEE Transactions on Services Computing
13
(4)
, pp. 639-652.
10.1109/TSC.2019.2963309
|
Abstract
In modern information systems different information features, about the same individual, are often collected and managed
by autonomous data collection services that may have different privacy policies. Answering many end-users’ legitimate queries requires
the integration of data from multiple such services. However, data integration is often hindered by the lack of a trusted entity, often
called a mediator, with which the services can share their data and delegate the enforcement of their privacy policies. In this paper, we
propose a flexible privacy-preserving data integration approach for answering data integration queries without the need for a trusted
mediator. In our approach, services are allowed to enforce their privacy policies locally. The mediator is considered to be untrusted,
and only has access to encrypted information to allow it to link data subjects across the different services. Services, by virtue of a new
privacy requirement, dubbed k-Protection, limiting privacy leaks, cannot infer information about the data held by each other. End-users,
in turn, have access to privacy-sanitized data only. We evaluated our approach using an example and a real dataset from the
healthcare application domain. The results are promising from both the privacy preservation and the performance perspectives.
Item Type: |
Article
|
Date Type: |
Publication |
Status: |
Published |
Schools: |
Computer Science & Informatics |
Publisher: |
Institute of Electrical and Electronics Engineers |
ISSN: |
1939-1374 |
Date of First Compliant Deposit: |
2 January 2020 |
Date of Acceptance: |
21 December 2019 |
Last Modified: |
25 Nov 2020 10:41 |
URI: |
http://orca.cf.ac.uk/id/eprint/128149 |
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