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Volumn , Issue , 2013, Pages 281-284

Geometry of privacy and utility

(2)  Lin, Bing Rong a   Kifer, Daniel a  

a NONE

Author keywords

[No Author keywords available]

Indexed keywords

COMMON PROPERTY; DESIGN OF ALGORITHMS; GEOMETRIC CHARACTERISTICS; PRIVACY PRESERVING; STATISTICAL PRIVACY; UTILITY MEASURE;

EID: 84897726200     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GlobalSIP.2013.6736870     Document Type: Conference Paper
Times cited : (6)

References (6)
  • 1
    • 33746086554 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, 2006.
    • (2006) TCC
    • Dwork, C.1    McSherry, F.2    Nissim, K.3    Smith, A.4
  • 2
    • 84862624687 scopus 로고    scopus 로고
    • A rigorous and customizable framework for privacy
    • D. Kifer and A. Machanavajjhala, "A rigorous and customizable framework for privacy," in PODS, 2012.
    • (2012) PODS
    • Kifer, D.1    Machanavajjhala, A.2
  • 4
    • 35448955271 scopus 로고    scopus 로고
    • Smooth sensitivity and sampling in private data analysis
    • K. Nissim, S. Raskhodnikova, and A. Smith, "Smooth sensitivity and sampling in private data analysis," in STOC, 2007.
    • (2007) STOC
    • Nissim, K.1    Raskhodnikova, S.2    Smith, A.3
  • 5
    • 84876784852 scopus 로고    scopus 로고
    • An axiomatic view of statistical privacy and utility
    • D. Kifer and B.-R. Lin, "An axiomatic view of statistical privacy and utility," J. of Privacy and Confidentiality, vol. 4, no. 1, 2012.
    • (2012) J. of Privacy and Confidentiality , vol.4 , Issue.1
    • Kifer, D.1    Lin, B.-R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.