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Volumn 4426 LNAI, Issue , 2007, Pages 84-95

Deriving private information from arbitrarily projected data

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; INDEPENDENT COMPONENT ANALYSIS; PERTURBATION TECHNIQUES;

EID: 38049165825     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71701-0_11     Document Type: Conference Paper
Times cited : (21)

References (13)
  • 3
    • 0032612381 scopus 로고    scopus 로고
    • High-order contrasts for independent component analysis
    • J. Cardoso. High-order contrasts for independent component analysis. Neural Computation, 11(1):157-192, 1999.
    • (1999) Neural Computation , vol.11 , Issue.1 , pp. 157-192
    • Cardoso, J.1
  • 5
  • 11
    • 31344447750 scopus 로고    scopus 로고
    • Random projection based multiplicative data perturbation for privacy preserving distributed data mining
    • K. Liu, H. Kargupta, and J. Ryan. Random projection based multiplicative data perturbation for privacy preserving distributed data mining. IEEE Transaction on Knowledge and Data Engineering, 18(1):92-106, 2006.
    • (2006) IEEE Transaction on Knowledge and Data Engineering , vol.18 , Issue.1 , pp. 92-106
    • Liu, K.1    Kargupta, H.2    Ryan, J.3
  • 12
    • 0033207750 scopus 로고    scopus 로고
    • A general additive data perturbation method for database security
    • K. Muralidhar and R. Sarathy. A general additive data perturbation method for database security. Management Science, 45(10):1399-1415, 1999.
    • (1999) Management Science , vol.45 , Issue.10 , pp. 1399-1415
    • Muralidhar, K.1    Sarathy, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.