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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sankar, L. Rajagopalan, S.R. Poor, H.V. |
| Copyright Year | 2010 |
| Description | Author affiliation: HP Labs, Princeton, NJ 08544 (Rajagopalan, S.R.) || Dept. of Electrical Engineering, Princeton University, Princeton, NJ 08544. lalitha (Sankar, L.; Poor, H.V.) |
| Abstract | The problem of private information “leakage” (inadvertently or by malicious design) from the myriad large centralized searchable data repositories drives the need for an analytical framework that quantifies unequivocally how safe private data can be (privacy) while still providing useful benefit (utility) to multiple legitimate information consumers. Rate distortion theory is shown to be a natural choice to develop such a framework which includes the following: modeling of data sources, developing application independent utility and privacy metrics, quantifying utility-privacy tradeoffs irrespective of the type of data sources or the methods of providing privacy, developing a side-information model for dealing with questions of external knowledge, and studying a successive disclosure problem for multiple query data sources. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 383022 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424470129 |
| e-ISBN | 9781424470143 |
| DOI | 10.1109/ITA.2010.5454092 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-01-31 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Data privacy Publishing Databases Social network services Humans Rate distortion theory Credit cards Information technology Information analysis Business |
| Content Type | Text |
| Resource Type | Article |
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