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Volumn , Issue , 2012, Pages 38-39

Recursive partitioning and summarization: A practical framework for differentially private data publishing

Author keywords

[No Author keywords available]

Indexed keywords

DATA CURATORS; DATA SETS; PRIVACY PRESERVING; PRIVATE DATA; PRIVATE DATA ANALYSIS; RECURSIVE PARTITIONING; SENSITIVE INFORMATIONS;

EID: 84871946312     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2414456.2414477     Document Type: Conference Paper
Times cited : (12)

References (18)
  • 3
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    • I. Dinur and K. Nissim. Revealing information while preserving privacy. In PODS, pages 202-210, 2003.
    • (2003) PODS , pp. 202-210
    • Dinur, I.1    Nissim, K.2
  • 4
    • 33746335051 scopus 로고    scopus 로고
    • Differential privacy
    • C. Dwork. Differential privacy. In ICALP, pages 1-12, 2006.
    • (2006) ICALP , pp. 1-12
    • Dwork, C.1
  • 5
    • 33745556605 scopus 로고    scopus 로고
    • Calibrating noise to sensitivity in private data analysis
    • C. Dwork, F. McSherry, K. Nissim, and A. Smith. Calibrating noise to sensitivity in private data analysis. In TCC, pages 265-284, 2006.
    • (2006) TCC , pp. 265-284
    • Dwork, C.1    McSherry, F.2    Nissim, K.3    Smith, A.4
  • 6
    • 51849089628 scopus 로고    scopus 로고
    • New efficient attacks on statistical disclosure control mechanisms
    • C. Dwork and S. Yekhanin. New efficient attacks on statistical disclosure control mechanisms. Advances in Cryptology-CRYPTO 2008, pages 469-480, 2008.
    • (2008) Advances in Cryptology-CRYPTO 2008 , pp. 469-480
    • Dwork, C.1    Yekhanin, S.2
  • 8
    • 77951192010 scopus 로고    scopus 로고
    • Accurate estimation of the degree distribution of private networks
    • M. Hay, C. Li, G. Miklau, and D. Jensen. Accurate Estimation of the Degree Distribution of Private Networks. In ICDM, pages 169-178, 2009.
    • (2009) ICDM , pp. 169-178
    • Hay, M.1    Li, C.2    Miklau, G.3    Jensen, D.4
  • 9
    • 78650518102 scopus 로고    scopus 로고
    • Boosting the accuracy of differentially private histograms through consistency
    • September
    • M. Hay, V. Rastogi, G. Miklau, and D. Suciu. Boosting the accuracy of differentially private histograms through consistency. Proc. VLDB Endow., 3:1021-1032, September 2010.
    • (2010) Proc. VLDB Endow. , vol.3 , pp. 1021-1032
    • Hay, M.1    Rastogi, V.2    Miklau, G.3    Suciu, D.4
  • 10
    • 84865663496 scopus 로고    scopus 로고
    • Releasing search queries and clicks privately
    • A. Korolova, K. Kenthapadi, N. Mishra, and A. Ntoulas. Releasing search queries and clicks privately. In WWW, pages 171-180, 2009.
    • (2009) WWW , pp. 171-180
    • Korolova, A.1    Kenthapadi, K.2    Mishra, N.3    Ntoulas, A.4
  • 11
    • 33749606641 scopus 로고    scopus 로고
    • Mondrian multidimensional k-anonymity
    • K. LeFevre, D. DeWitt, and R. Ramakrishnan. Mondrian multidimensional k-anonymity. In ICDE, page 25, 2006.
    • (2006) ICDE , pp. 25
    • LeFevre, K.1    DeWitt, D.2    Ramakrishnan, R.3
  • 12
    • 34548805858 scopus 로고    scopus 로고
    • T-closeness: Privacy beyond k-anonymity and l-diversity
    • N. Li, T. Li, and S. Venkatasubramanian. t-closeness: Privacy beyond k-anonymity and l-diversity. In ICDE, pages 106-115, 2007.
    • (2007) ICDE , pp. 106-115
    • Li, N.1    Li, T.2    Venkatasubramanian, S.3
  • 14
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    • Mechanism design via differential privacy
    • F. McSherry and K. Talwar. Mechanism design via differential privacy. In FOCS, pages 94-103, 2007.
    • (2007) FOCS , pp. 94-103
    • McSherry, F.1    Talwar, K.2
  • 15
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    • Robust de-anonymization of large sparse datasets
    • A. Narayanan and V. Shmatikov. Robust de-anonymization of large sparse datasets. In S&P, pages 111-125, 2008.
    • (2008) S&P , pp. 111-125
    • Narayanan, A.1    Shmatikov, V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.