k-ARQ: K-anonymous ranking queries

Eunjin Jung, Sukhyun Ahn, Seung Won Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


With the advent of an unprecedented magnitude of data, top-k queries have gained a lot of attention. However, existing work to date has focused on optimizing efficiency without looking closely at privacy preservation. In this paper, we study how existing approaches have failed to support a combination of accuracy and privacy requirements and we propose a new data publishing framework that supports both areas. We show that satisfying both requirements is an essential problem and propose two comprehensive algorithms. We also validated the correctness and efficiency of our approach using experiments.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 15th International Conference, DASFAA 2010, Proceedings
Number of pages15
EditionPART 1
Publication statusPublished - 2010
Event15th International Conference on Database Systems for Advanced Applications, DASFAA 2010 - Tsukuba, Japan
Duration: 2010 Apr 12010 Apr 4

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5981 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other15th International Conference on Database Systems for Advanced Applications, DASFAA 2010

Bibliographical note

Funding Information:
This work was supported by Engineering Research Center of Excellence Program of Korea Ministry of Education, Science and Technology (MEST) / Korea Science and Engineering Foundation (KOSEF), grant number R11-2008-007-03003-0.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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