Abstract
Using a broadcast channel to transmit clients' data requests may impose privacy risks. In this paper, we tackle such privacy concerns in the index coding framework. We show how a curious client can infer some information about the requests and side information of other clients by learning the encoding matrix used by the server. We propose an information-theoretic metric to measure the level of privacy and show how encoding matrices can be designed to achieve specific privacy guarantees. We then consider a special scenario for which we design a transmission scheme and derive the achieved levels of privacy in closed-form. We also derive upper bounds and we compare them to the levels of privacy achieved by our scheme, highlighting that an inherent trade-off exists between protecting privacy of the request and of the side information of the clients.
Original language | English (US) |
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Title of host publication | 2017 IEEE International Symposium on Information Theory, ISIT 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2543-2547 |
Number of pages | 5 |
ISBN (Electronic) | 9781509040964 |
DOIs | |
State | Published - Aug 9 2017 |
Event | 2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany Duration: Jun 25 2017 → Jun 30 2017 |
Publication series
Name | IEEE International Symposium on Information Theory - Proceedings |
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ISSN (Print) | 2157-8095 |
Other
Other | 2017 IEEE International Symposium on Information Theory, ISIT 2017 |
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Country/Territory | Germany |
City | Aachen |
Period | 6/25/17 → 6/30/17 |
Bibliographical note
Funding Information:The work of the authors was partially funded by NSF under Awards 1423271, 1527550 and 1314937.
Publisher Copyright:
© 2017 IEEE.