TY - GEN
T1 - Entropy-minimizing mechanism for differential privacy of discrete-time linear feedback systems
AU - Wang, Yu
AU - Huang, Zhenqi
AU - Mitra, Sayan
AU - Dullerud, Geir E.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - The concept of differential privacy stems from the study of private query of datasets. In this work, we apply this concept to metric spaces to study a mechanism that randomizes a deterministic query by adding mean-zero noise to keep differential privacy. For one-shot queries, we show that -differential privacy of an n-dimensional input implies a lower bound n - n ln(/2) on the entropy of the randomized output, and this lower bound is achieved by adding Laplacian noise. We then consider the -differential privacy of a discrete-time linear feedback system in which noise is added to the system output at each time. The adversary estimates the system states from the output history. We show that, to keep the system -differentially private, the output entropy is bounded below, and this lower bound is achieves by an explicit mechanism.
AB - The concept of differential privacy stems from the study of private query of datasets. In this work, we apply this concept to metric spaces to study a mechanism that randomizes a deterministic query by adding mean-zero noise to keep differential privacy. For one-shot queries, we show that -differential privacy of an n-dimensional input implies a lower bound n - n ln(/2) on the entropy of the randomized output, and this lower bound is achieved by adding Laplacian noise. We then consider the -differential privacy of a discrete-time linear feedback system in which noise is added to the system output at each time. The adversary estimates the system states from the output history. We show that, to keep the system -differentially private, the output entropy is bounded below, and this lower bound is achieves by an explicit mechanism.
UR - http://www.scopus.com/inward/record.url?scp=84988274715&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988274715&partnerID=8YFLogxK
U2 - 10.1109/CDC.2014.7039713
DO - 10.1109/CDC.2014.7039713
M3 - Conference contribution
AN - SCOPUS:84988274715
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 2130
EP - 2135
BT - 53rd IEEE Conference on Decision and Control,CDC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Y2 - 15 December 2014 through 17 December 2014
ER -