01456nas a2200145   4500008004100000245006500041210006400106260003300170520092200203100002401125700001701149700002001166700002201186856010201208       2014                        eng d00aAnti-discrimination analysis using privacy attack strategies0 aAntidiscrimination analysis using privacy attack strategies  bSpringer, Berlin, Heidelberg3 aSocial 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.1 aRuggieri, Salvatore1 aHajian, Sara1 aKamiran, Faisal1 aZhang, Xiangliang  uhttps://kdd.isti.cnr.it/publications/anti-discrimination-analysis-using-privacy-attack-strategies