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Volumn , Issue , 2007, Pages 136-145

On randomization, public information and the curse of dimensionality

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; DATA MINING; PERTURBATION TECHNIQUES;

EID: 34548797068     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2007.367859     Document Type: Conference Paper
Times cited : (51)

References (12)
  • 2
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    • On the Design and Quantification of Privacy Preserving Data Mining Algorithms
    • Agrawal D. Aggarwal C. C. On the Design and Quantification of Privacy Preserving Data Mining Algorithms. ACM PODS Conference, 2002.
    • (2002) ACM PODS Conference
    • Agrawal, D.1    Aggarwal, C.C.2
  • 3
    • 33745629638 scopus 로고    scopus 로고
    • On k-anonymity and the curse of dimensionality
    • Aggarwal C. C. On k-anonymity and the curse of dimensionality. VLDB Conference, 2005.
    • (2005) VLDB Conference
    • Aggarwal, C.C.1
  • 4
    • 29844443183 scopus 로고    scopus 로고
    • To Do or Not To Do: The Dilemma of Disclosing Anonymized Data
    • Lakshmanan L., Ng R., Ramesh G. To Do or Not To Do: The Dilemma of Disclosing Anonymized Data. ACM SIGMOD Conference, 2005.
    • (2005) ACM SIGMOD Conference
    • Lakshmanan, L.N.R.1    Ramesh, G.2
  • 7
    • 0022130080 scopus 로고
    • A data distortion by probability distribution
    • Liew C. K., Choi U. J., Liew C. J. A data distortion by probability distribution. ACM TODS, 10(3):395-411, 1985.
    • (1985) ACM TODS , vol.10 , Issue.3 , pp. 395-411
    • Liew, C.K.1    Choi, U.J.2    Liew, C.J.3
  • 8
    • 29844458622 scopus 로고    scopus 로고
    • Deriving Private Information from Randomized Data
    • Huang Z., Du W., Chen B. Deriving Private Information from Randomized Data. pp. 37-48, ACM SIGMOD Conference, 2005.
    • (2005) ACM SIGMOD Conference , pp. 37-48
    • Huang, Z.D.W.1    Chen, B.2
  • 9
    • 78149340011 scopus 로고    scopus 로고
    • On the Privacy Preserving Properties of Random Data Perturbation Techniques
    • Kargupta H., Datta S., Wang Q., Sivakumar K. On the Privacy Preserving Properties of Random Data Perturbation Techniques. ICDM Conference, pp. 99-106, 2003.
    • (2003) ICDM Conference , pp. 99-106
    • Kargupta, H.1    Datta, S.2    Wang, Q.3    Sivakumar, K.4
  • 10
    • 1142294784 scopus 로고    scopus 로고
    • Maintaining Data Privacy in Association Rule Mining
    • Rizvi S., Haritsa J. Maintaining Data Privacy in Association Rule Mining. VLDB Conference, 2002.
    • (2002) VLDB Conference
    • Rizvi, S.1    Haritsa, J.2
  • 11
    • 0035517699 scopus 로고    scopus 로고
    • Protecting Respondents' Identities in Microdata Release
    • Samarati P.: Protecting Respondents' Identities in Microdata Release. IEEE Trans. Knowl. Data Eng. 13(6): 1010-1027 (2001).
    • (2001) IEEE Trans. Knowl. Data Eng , vol.13 , Issue.6 , pp. 1010-1027
    • Samarati, P.1
  • 12
    • 11844281385 scopus 로고    scopus 로고
    • State-of-the-art in privacy preserving data, mining
    • Verykios V. S. et al. State-of-the-art in privacy preserving data, mining. ACM SIGMOD Record, v.33 n.1, 2004
    • (2004) ACM SIGMOD Record , vol.33 , Issue.1
    • Verykios, V.S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.