A Survey of Quantification of Privacy Preserving Data Mining Algorithms

By Elisa Bertino, Dan Lin, Wei Jiang. 2008

171 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Science Applications, Sociology and Political Science

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jaideep Vaidya
2. Chris Clifton
3. Yu Zhu
4. Isabel Wagner
5. David Eckhoff
6. Vitaly Shmatikov
7. Reza Shokri
8. Jayant R. Haritsa

In Computer Science Applications

1. Isabel Wagner
2. Jaideep Vaidya
3. Yu Zhu
4. Chris Clifton
5. David Eckhoff

In Sociology and Political Science

1. Isabel Wagner
2. Jaideep Vaidya
3. Yu Zhu
4. Chris Clifton
5. David Eckhoff

Citations in the corpus

• Privacy Preserving Data Mining (2015, background): “An important aspect in such algorithms design is identifying evaluation criteria and developing related benchmarks (Bertino et al ., 2008).”
• Technical Privacy Metrics (2015, background): “[16] require that privacy metrics indicate the privacy level, the portion of sensitive data that is not hidden, and the data quality after application of the PET.”