Name
Abstract | ||
|---|---|---|
Massive amounts of data are being collected, stored, and analyzed for various business and marketing purposes. While such data analysis is critical for many applications, it could also violate the privacy of individuals. This paper describes the issues involved in designing a privacy aware data management framework for collecting, storing, and analyzing the data. We also discuss behavioral aspects of data sharing as well as aspects of a formal framework based on rewriting rules that encompasses the privacy aware data management framework.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3205977.3205997 | SACMAT '18: The 23rd ACM Symposium on Access Control Models and Technologies
Indianapolis
Indiana
USA
June, 2018 |
Keywords | Field | DocType |
Data privacy,quantified self,privacy preserving,data analytics | Data science,Data analysis,Computer security,Computer science,Data sharing,Rewriting,Information privacy,Data management | Conference |
ISBN | Citations | PageRank |
978-1-4503-5666-4 | 3 | 0.46 |
References | Authors | |
37 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bhavani M. Thuraisingham | 1 | 2587 | 282.14 |
| Murat Kantarcioglu | 2 | 2470 | 168.03 |
| Elisa Bertino | 3 | 14025 | 2128.50 |
| Jonathan Z. Bakdash | 4 | 30 | 5.99 |
| Maribel Fernández | 5 | 315 | 23.44 |