k -Anonymous Data Mining: A Survey
By Valentina Ciriani, Sabrina De Capitani di Vimercati, Sara Foresti, Pierangela Samarati. 2008
100 citations recorded by the source corpus.
Subfields: Artificial Intelligence, 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
- Jiankun Hu
- Yanming Zhu
- Mazleena Salleh
- Yousra Abdul Alsahib S. Aldeen
- Xuefei Yin
- Mohammad Abdur Razzaque
In Sociology and Political Science
- Jiankun Hu
- Yanming Zhu
- Mazleena Salleh
- Yousra Abdul Alsahib S. Aldeen
- Xuefei Yin
- Mohammad Abdur Razzaque
Citations in the corpus
- Privacy Preserving Data Mining (2015, neutral): “(1) and (2): (Ciriani et al ., 2008).”
- A Comprehensive Survey of Privacy-preserving Federated Learning (2021, methodology): “The first core component is to apply the k-anonymity scheme [33] on the original private data on the client side and utilize the anonymized data to collaboratively train a global model.”
- A comprehensive review on privacy preserving data mining (2015, methodology): “Ciriani et al. (2008) highlighted the potential threats to K-ano-nymity, which are raised via the implementation of mining to collect data and analyses of two main techniques to join K-anonymity in data mining.”