Injecting purpose and trust into data anonymisation
Poster
Paper/Presentation Title | Injecting purpose and trust into data anonymisation |
---|---|
Presentation Type | Poster |
Authors | Sun, Xiaoxun (Author), Wang, Hua (Author) and Li, Jiuyong (Author) |
Editors | Cheung, David, Song, Il-Yeol, Chu, Wesley, Hu, Xiaohua and Lin, Jimmy |
Journal or Proceedings Title | Proceedings of the 18th ACM International Conference on Information and Knowledge Management (CIKM 2009) |
Number of Pages | 3 |
Year | 2009 |
Place of Publication | New York, USA |
ISBN | 9781605585123 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/1645953.1646166 |
Web Address (URL) of Paper | http://portal.acm.org/ft_gateway.cfm?id=1646166&type=pdf&coll=GUIDE&dl=GUIDE&CFID=66996010&CFTOKEN=17096199 |
Conference/Event | 18th ACM International Conference on Information and Knowledge Management (CIKM 2009) |
Event Details | 18th ACM International Conference on Information and Knowledge Management (CIKM 2009) Event Date 02 to end of 06 Nov 2009 Event Location Hong Kong, China |
Abstract | Most existing works of data anonymisation target at the optimization of the anonymisation metrics to balance the data utility and privacy, whereas they ignore the effects of a requester's trust level and application purposes during the data anonymisation. Our aim of this paper is to propose a much finer level anonymisation scheme with regard to the data requester's trust value and specific application purpose. We prioritize the attributes for anonymisation based on how important and critical they are related to the specified application purposes and propose a trust evaluation strategy to quantify the data requester's reliability, and further build the projection between the trust value and the degree of data anonymiztion, which intends to determine to what extent the data should be anonymizd. The decomposition algorithm is developed to find the desired anonymous solution, which guarantees the uniqueness and correctness |
Keywords | anonymization; privacy; trust; algorithms; security |
ANZSRC Field of Research 2020 | 460599. Data management and data science not elsewhere classified |
461399. Theory of computation not elsewhere classified | |
460499. Cybersecurity and privacy not elsewhere classified | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Department of Mathematics and Computing |
University of South Australia |
https://research.usq.edu.au/item/9z5w5/injecting-purpose-and-trust-into-data-anonymisation
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