Brussels, Belgium Belgium
Dec. 10, 2012 to Dec. 10, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2012.19
In last years, data mining has raised some concerns related to privacy invasion of the individuals and potential discrimination based on the extracted patterns and profiles. Efforts at fighting against these risks have led to developing privacy preserving data mining (PPDM) techniques and anti-discrimination techniques in data mining. However, there is an evident gap between the large body of research in data privacy technologies and the recent early results on anti-discrimination technologies. This context presents a study on the relation between data anonymization from privacy technologies literature and anti-discrimination. We discuss how different data anonymization techniques have impact on discriminatory biased datasets.
Data privacy, Itemsets, Context, Data models, Legislation, Privacy, Classification rules, Privacy, Anti-discrimination, Data anonymization, Generalization, Suppression
Sara Hajian, Josep Domingo-Ferrer, "A Study on the Impact of Data Anonymization on Anti-discrimination", ICDMW, 2012, 2013 IEEE 13th International Conference on Data Mining Workshops, 2013 IEEE 13th International Conference on Data Mining Workshops 2012, pp. 352-359, doi:10.1109/ICDMW.2012.19