Name
Abstract | ||
|---|---|---|
We consider a cloud-based control framework in which individual clients own their local plants that must be controlled by a public authority. Individual clients desire to keep the local state information as private as possible, as long as the cloud-based controller can provide a given level of quality of service. Based on an axiomatic argument, we show that Kramer's notion of causally conditioned directed information from the state random variable to a random variable disclosed to the public authority is an appropriate measure of privacy loss. For a special case with the Linear-Quadratic-Gaussian (LQG) setting, we provide a procedure to construct a "privacy filter" that attains the optimal trade-off between privacy loss and control quality. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 AMERICAN CONTROL CONFERENCE (ACC) | Internet privacy,Linear-quadratic-Gaussian control,Privacy by Design,Computer science,Computer security,Quality of service,Mutual information,Information privacy,Privacy software,Cloud computing,Special case |
DocType | ISSN | Citations |
Conference | 0743-1619 | 2 |
PageRank | References | Authors |
0.36 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takashi Tanaka | 1 | 34 | 12.22 |
| Mikael Skoglund | 2 | 1397 | 175.71 |
| Henrik Sandberg | 3 | 1215 | 112.50 |
| Karl Henrik Johansson | 4 | 3996 | 322.75 |