Assessing global disclosure risk in masked microdata

By Traian Marius Truta, F. Fotouhi, D. Barth-Jones. 2004

19 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research

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. Fida Kamal Dankar
2. K. El Emam
3. Sushil Jajodia
4. Ajit Appari
5. Hongkyu Park
6. M. Eric Johnson
7. Mahmoud Mohammadi
8. Kshitij Gorde

In Information Systems

1. Sushil Jajodia
2. Ajit Appari
3. M. Eric Johnson
4. K. El Emam

In Management Science and Operations Research

1. Ajit Appari
2. M. Eric Johnson
3. Fida Kamal Dankar
4. K. El Emam

Citations in the corpus

• Data Synthesis based on Generative Adversarial Networks (2018, methodology): “The authors of [34] proposed a risk evaluation method based on entropy.”
• A method for evaluating marketer re-identification risk (2010, background): “In another study, Truta et al [34] presented a measure of disclosure risk that considers the distribution of the non-unique records in the sample.”
• Information security and privacy in healthcare: current state of research (2010, methodology): “In another study, Truta et al. (2004a) considered a data-sampling method to assess its performance with respect to the above-mentioned three risk measures.”