Name
Abstract | ||
|---|---|---|
Big data is widely considered as the next big trend in e-Government environments but at the same time one of the most emerging and critical issues due to the challenges it imposes. The large amount of data being retained by governmental Service Providers that can be (potentially) exploited during Data Mining and analytics processes, include personal data and personally identifiable information, raising privacy concerns, mostly regarding data minimization and purpose limitation. This paper addresses the consideration of Central Government to aggregate information without revealing personal identifiers of individuals and proposes a privacy preserving methodology that can be easily incorporated into already deployed electronic services and e-Government frameworks through the adoption of scalable and adaptable salted hashing techniques. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-22906-5_16 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Privacy,Anonymity,Big data,Data mining,e-Government | Internet privacy,Identifier,Computer science,Computer security,Service provider,Central government,Personally identifiable information,Anonymity,Information privacy,Analytics,Big data | Conference |
Volume | ISSN | Citations |
9264 | 0302-9743 | 3 |
PageRank | References | Authors |
0.44 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prokopios Drogkaris | 1 | 10 | 2.35 |
| Aristomenis Gritzalis | 2 | 5 | 1.15 |