Name
Title | ||
|---|---|---|
The influence of dataset characteristics on privacy preserving methods in the advanced metering infrastructure. |
Abstract | ||
|---|---|---|
The computing and communication devices employed by the cyber-physical IoT-enabled systems generate large quantities of data. These data offer new possibilities but also raise a number of challenges, especially through their social implications. One of these challenges is preserving the privacy of the individuals whose behavior generates the data in question. Studying how the characteristics of these large datasets may influence the efficiency of different privacy enhancing methods is important. Stakeholders can then better understand the properties of their datasets and the conditions under which such datasets can be released to third parties. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cose.2018.02.012 | Computers & Security |
Keywords | Field | DocType |
Advanced metering infrastructure,Data privacy,Data characteristics,De-anonymization,De-pseudonymization | Data collection,Computer security,Computer science,Granularity,Adversary,Metering mode,Probabilistic framework | Journal |
Volume | ISSN | Citations |
76 | 0167-4048 | 1 |
PageRank | References | Authors |
0.37 | 23 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Valentin Tudor | 1 | 14 | 2.70 |
| Magnus Almgren | 2 | 270 | 39.17 |
| Marina Papatriantafilou | 3 | 316 | 45.72 |