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Volumn , Issue , 2007, Pages 380-387

K-anonymization incremental maintenance and optimization techniques

Author keywords

Clustering; Incremental; K anonymity; Optimization; Privacy

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTATIONAL METHODS; DATA PRIVACY; PREVENTIVE MAINTENANCE; REAL TIME SYSTEMS;

EID: 35248876111     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1244002.1244093     Document Type: Conference Paper
Times cited : (39)

References (22)
  • 3
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    • Byun, J.W., Kamra, A., Bertino, E, and Li, N., Efficient k-Anonymity using Clustering Technique, CERIAS Tech Report 2006-10, 2006a.
    • Byun, J.W., Kamra, A., Bertino, E, and Li, N., Efficient k-Anonymity using Clustering Technique, CERIAS Tech Report 2006-10, 2006a.
  • 5
    • 20244376130 scopus 로고    scopus 로고
    • Pre-proc. of ETK-NTTS'2001 (vol. 2), Luxembourg: Eurostat
    • Domingo-Ferrer, J., Mateo-Sanz, J., and Torra, V., Comparing SDC Methods for Microdata on the Basis of Information Loss and Disclosure Risk, Pre-proc. of ETK-NTTS'2001 (vol. 2), Luxembourg: Eurostat, 2001, 807-826.
    • (2001) , pp. 807-826
    • Domingo-Ferrer, J.1    Mateo-Sanz, J.2    Torra, V.3
  • 10
    • 29844444250 scopus 로고    scopus 로고
    • Incognito: Efficient Full-Domain k-Anonymity
    • Baltimore, Maryland
    • LeFevre, K., DeWitt, D., and Ramakrishnan, R., Incognito: Efficient Full-Domain k-Anonymity, Proc. of the ACM SIGMOD, Baltimore, Maryland, 2005, 49-60.
    • (2005) Proc. of the ACM SIGMOD , pp. 49-60
    • LeFevre, K.1    DeWitt, D.2    Ramakrishnan, R.3
  • 13
    • 33749607006 scopus 로고    scopus 로고
    • Machanavajjhala, A., Gehrke, J., and Kifer, D., l-diversity: privacy beyond k-anonymity, Proc. of the 22nd IEEE Intl. Conference on Data Eng., 2006.
    • Machanavajjhala, A., Gehrke, J., and Kifer, D., l-diversity: privacy beyond k-anonymity, Proc. of the 22nd IEEE Intl. Conference on Data Eng., 2006.
  • 14
    • 26944480003 scopus 로고    scopus 로고
    • Probabilistic Information Loss Measures in Confidentiality Protection of Continuous Microdata
    • Mateo-Sanz, J.M., Domingo-Ferrer, J., and Sebe, F., Probabilistic Information Loss Measures in Confidentiality Protection of Continuous Microdata, Data Mining and Knowledge Discovery, Vol. 11, No. 2, 2005, 181-193.
    • (2005) Data Mining and Knowledge Discovery , vol.11 , Issue.2 , pp. 181-193
    • Mateo-Sanz, J.M.1    Domingo-Ferrer, J.2    Sebe, F.3
  • 15
    • 3142691086 scopus 로고    scopus 로고
    • On the Complexity of Optimal k-Anonymity
    • Meyerson A., and Williams R., On the Complexity of Optimal k-Anonymity, ACM PODS Conf, 2004, 223-228.
    • (2004) ACM PODS Conf , pp. 223-228
    • Meyerson, A.1    Williams, R.2
  • 17
    • 0035517699 scopus 로고    scopus 로고
    • Protecting Respondents Identities in Microdata Release
    • Samarati P., Protecting Respondents Identities in Microdata Release, IEEE Transactions on Knowledge and Data Eng., Vol. 13, No. 6, 2001, 1010-1027.
    • (2001) IEEE Transactions on Knowledge and Data Eng , vol.13 , Issue.6 , pp. 1010-1027
    • Samarati, P.1
  • 19
    • 0036811143 scopus 로고    scopus 로고
    • Achieving k-Anonymity Privacy Protection Using Generalization and Suppression
    • Sweeney L., Achieving k-Anonymity Privacy Protection Using Generalization and Suppression, Intl. Journal on Uncertainty, Fuzziness, and Knowledge-based Systems, Vol. 10, No. 5, 2002b, 571-588.
    • (2002) Intl. Journal on Uncertainty, Fuzziness, and Knowledge-based Systems , vol.10 , Issue.5 , pp. 571-588
    • Sweeney, L.1
  • 22


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.