Show simple item record

dc.contributor.authorRuggieri, Salvatore
dc.contributor.authorHajian, Sara
dc.contributor.authorKamiran, Faisal
dc.contributor.authorZhang, Xiangliang
dc.date.accessioned2015-06-10T11:41:12Z
dc.date.available2015-06-10T11:41:12Z
dc.date.issued2014-09-01
dc.identifier.citationRuggieri, S., Hajian, S., Kamiran, F., & Zhang, X. (2014). Anti-discrimination Analysis Using Privacy Attack Strategies. Lecture Notes in Computer Science, 694–710. doi:10.1007/978-3-662-44851-9_44
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/978-3-662-44851-9_44
dc.identifier.urihttp://hdl.handle.net/10754/556651
dc.description.abstractSocial discrimination discovery from data is an important task to identify illegal and unethical discriminatory patterns towards protected-by-law groups, e.g., ethnic minorities. We deploy privacy attack strategies as tools for discrimination discovery under hard assumptions which have rarely tackled in the literature: indirect discrimination discovery, privacy-aware discrimination discovery, and discrimination data recovery. The intuition comes from the intriguing parallel between the role of the anti-discrimination authority in the three scenarios above and the role of an attacker in private data publishing. We design strategies and algorithms inspired/based on Frèchet bounds attacks, attribute inference attacks, and minimality attacks to the purpose of unveiling hidden discriminatory practices. Experimental results show that they can be effective tools in the hands of anti-discrimination authorities.
dc.publisherSpringer Nature
dc.relation.urlhttp://link.springer.com/chapter/10.1007%2F978-3-662-44851-9_44
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-662-44851-9_44
dc.titleAnti-discrimination Analysis Using Privacy Attack Strategies
dc.typeConference Paper
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalMachine Learning and Knowledge Discovery in Databases
dc.conference.date2014-09-15 to 2014-09-19
dc.conference.nameEuropean Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2014
dc.conference.locationNancy, FRA
dc.eprint.versionPost-print
dc.contributor.institutionUniversità di Pisa, Italy
dc.contributor.institutionUniversitat Rovira i Virgili, Spain
dc.contributor.institutionInformation Technology, University of the Punjab, Pakistan
kaust.personZhang, Xiangliang
refterms.dateFOA2015-09-15T00:00:00Z
dc.date.published-online2014-09-01
dc.date.published-print2014


Files in this item

Thumbnail
Name:
Anti-discrimination analysis.pdf
Size:
487.8Kb
Format:
PDF
Description:
Accepted Manuscript

This item appears in the following Collection(s)

Show simple item record