Abstract
We examine a tradeoff between privacy and utility in terms of local differential privacy (L-DP) and Hamming distortion for certain classes of finite-alphabet sources under Hamming distortion. We define two classes: permutation-invariant, and ordered statistics (whose probability mass functions are monotonic). We obtain the optimal L-DP mechanism for permutation-invariant sources and derive upper and lower bounds on the achievable local differential privacy for ordered statistics for a range of target distortion values.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2069-2073 |
| Number of pages | 5 |
| Volume | 2016-August |
| ISBN (Electronic) | 9781509018062 |
| DOIs | |
| State | Published - Aug 10 2016 |
| Event | 2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain Duration: Jul 10 2016 → Jul 15 2016 |
Other
| Other | 2016 IEEE International Symposium on Information Theory, ISIT 2016 |
|---|---|
| Country | Spain |
| City | Barcelona |
| Period | 7/10/16 → 7/15/16 |
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Keywords
- Differential Privacy
- Information Leakage
- utility-privacy tradeoff
ASJC Scopus subject areas
- Theoretical Computer Science
- Information Systems
- Modeling and Simulation
- Applied Mathematics
Cite this
Optimal differential privacy mechanisms under Hamming distortion for structured source classes. / Kalantari, Kousha; Sankar, Lalitha; Sarwate, Anand D.
Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. Vol. 2016-August Institute of Electrical and Electronics Engineers Inc., 2016. p. 2069-2073 7541663.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Optimal differential privacy mechanisms under Hamming distortion for structured source classes
AU - Kalantari, Kousha
AU - Sankar, Lalitha
AU - Sarwate, Anand D.
PY - 2016/8/10
Y1 - 2016/8/10
N2 - We examine a tradeoff between privacy and utility in terms of local differential privacy (L-DP) and Hamming distortion for certain classes of finite-alphabet sources under Hamming distortion. We define two classes: permutation-invariant, and ordered statistics (whose probability mass functions are monotonic). We obtain the optimal L-DP mechanism for permutation-invariant sources and derive upper and lower bounds on the achievable local differential privacy for ordered statistics for a range of target distortion values.
AB - We examine a tradeoff between privacy and utility in terms of local differential privacy (L-DP) and Hamming distortion for certain classes of finite-alphabet sources under Hamming distortion. We define two classes: permutation-invariant, and ordered statistics (whose probability mass functions are monotonic). We obtain the optimal L-DP mechanism for permutation-invariant sources and derive upper and lower bounds on the achievable local differential privacy for ordered statistics for a range of target distortion values.
KW - Differential Privacy
KW - Information Leakage
KW - utility-privacy tradeoff
UR - http://www.scopus.com/inward/record.url?scp=84985992114&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84985992114&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2016.7541663
DO - 10.1109/ISIT.2016.7541663
M3 - Conference contribution
AN - SCOPUS:84985992114
VL - 2016-August
SP - 2069
EP - 2073
BT - Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PB - Institute of Electrical and Electronics Engineers Inc.
ER -