On the linkability of complementary information from free versions of people databases

  • Authors:
  • Minaxi Gupta;Yuqing (Melanie) Wu;Swapnil S. Joshi;Aparna Tiwari;Ashish Nair;Ezhilan Ilangovan

  • Affiliations:
  • Indiana University;Indiana University;Indiana University;Indiana University;Indiana University;Indiana University

  • Venue:
  • ACM SIGMETRICS Performance Evaluation Review
  • Year:
  • 2013

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Abstract

The privacy of hundreds of millions of people today could be compromised due to people databases which claim to store many personal details about individuals, often without their knowledge. While the paid versions of these databases may be prohibitively expensive for data mining on a mass scale, in this paper, we show that even the limited information provided by the unpaid versions of these databases can be effectively exploited for its complementarity and poses a significant privacy threat since an adversary can mine this information on a mass scale free of cost and then use it to his/her advantage, hurting the privacy of individuals.