Name
Abstract | ||
|---|---|---|
As smart meters continue to be deployed around the world collecting unprecedented levels of fine-grained data about consumers, we need to find mechanisms that are fair to both, (1) the electric utility who needs the data to improve their operations, and (2) the consumer who has a valuation of privacy but at the same time benefits from sharing consumption data. In this paper we address this problem by proposing privacy contracts between electric utilities and consumers with the goal of maximizing the social welfare of both. Our mathematical model designs an optimization problem between a population of users that have different valuations on privacy and the costs of operation by the utility. We then show how contracts can change depending on the probability of a privacy breach. This line of research can help inform not only current but also future smart meter collection practices. |
Year | Venue | Field |
|---|---|---|
2014 | CoRR | Population,Mathematical optimization,Privacy by Design,Electric utility,Computer security,Risk analysis (engineering),Smart meter,Information privacy,Valuation (finance),Privacy software,Mathematics,Social Welfare |
DocType | Volume | Citations |
Journal | abs/1409.7926 | 3 |
PageRank | References | Authors |
0.45 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lillian J. Ratliff | 1 | 87 | 23.32 |
| Carlos Barreto | 2 | 31 | 5.15 |
| Roy Dong | 3 | 79 | 12.05 |
| Henrik Ohlsson | 4 | 305 | 25.91 |
| Alvaro A. Cárdenas | 5 | 1390 | 101.51 |
| Shankar Sastry | 6 | 11977 | 1291.58 |