Novel iterative min-max clustering to minimize information loss in statistical disclosure control
Paper
Paper/Presentation Title | Novel iterative min-max clustering to minimize information loss in statistical disclosure control |
---|---|
Presentation Type | Paper |
Authors | Mahmood, Abdun Naser (Author), Kabir, Md Enamul (Author) and Mustafa, Abdul K. (Author) |
Journal or Proceedings Title | Proceedings of the 10th International Conference on Security and Privacy in Communication Networks (SecureComm 2014) |
ERA Conference ID | 43516 |
Journal Citation | 153, pp. 157-172 |
Number of Pages | 16 |
Year | 2014 |
Place of Publication | Germany |
ISBN | 9783319238012 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-319-23802-9_14 |
Web Address (URL) of Paper | http://link.springer.com/chapter/10.1007%2F978-3-319-23802-9_14 |
Conference/Event | 10th International Conference on Security and Privacy in Communication Networks (SecureComm 2014) |
International Conference on Security and Privacy for Communication Networks | |
Event Details | International Conference on Security and Privacy for Communication Networks SecureCom Rank A A A A A A A A A A A A A A A A |
Event Details | 10th International Conference on Security and Privacy in Communication Networks (SecureComm 2014) Event Date 24 to end of 26 Sep 2014 Event Location Beijing, China |
Abstract | In recent years, there has been an alarming increase of online identity theft and attacks using personally identifiable information. The goal of privacy preservation is to de-associate individuals from sensitive or microdata information. Microaggregation techniques seeks to protect |
Keywords | privacy; microaggregation; microdata protection; k-anonymity disclosure control |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
460499. Cybersecurity and privacy not elsewhere classified | |
Public Notes | No evidence of copyright restrictions preventing deposit. |
Byline Affiliations | University of New South Wales |
University of Queensland | |
Humber College, Canada | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q3065/novel-iterative-min-max-clustering-to-minimize-information-loss-in-statistical-disclosure-control
Download files
1873
total views198
total downloads0
views this month0
downloads this month