Name
Abstract | ||
|---|---|---|
In recent years, a variety of privacy events emerges and bring huge losses. With the in-depth application of data mining, big data, cloud computing and other technology, privacy protection issue becomes more and more challenging. Therefore, we propose a privacy protection mechanism for sensitive group information. A reasonable counterfeit data set is constructed based on cloud model for sensitive features of group data to disguise real sensitive group features. The mechanism takes the data dependencies between multiple attributes into consideration, and reduces the amount of fake data added to improve the availability of data. The method we proposed is proved to be effective through analysis and experiments. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CIT/IUCC/DASC/PICOM.2015.146 | CIT/IUCC/DASC/PICOM 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY - UBIQUITOUS COMPUTING AND COMMUNICATIONS - DEPENDABLE, AUTONOMIC AND SECURE COMPUTING - PERVASIVE INTELLIGENCE AND COMPUTING |
Keywords | Field | DocType |
big data, cloud model, group privacy, data privacy, sensitive features | Protection mechanism,Data modeling,Computer security,Computer science,Cloud computing security,Information privacy,Counterfeit,Big data,Privacy software,Cloud computing | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruxiang Zhai | 1 | 0 | 0.34 |
| Kun Zhang | 2 | 0 | 0.34 |
| Mingjun Liu | 3 | 0 | 2.70 |