Digression and value concatenation to enable privacy-preserving regression

MIS Quarterly: Management Information Systems

Volumn 38, Issue 3, 2014, Pages 679-698

  Li, Xiao Bai ^a   Sarkar, Sumit ^b  

^a UNIVERSITY OF MASSACHUSETTS LOWELL   (United States)

^b UNIVERSITY OF TEXAS AT DALLAS   (United States)

Author keywords

Anonymization; Data analytics; Data mining; Privacy; Regression; Regression trees

Indexed keywords

DATA HANDLING; DATA MINING; FORESTRY; INFORMATION ANALYSIS; QUALITY CONTROL; REGRESSION ANALYSIS; RISK ASSESSMENT; TREES (MATHEMATICS);

ANONYMIZATION; DATA ANALYTICS; PRIVATE INFORMATION; REGRESSION; REGRESSION TECHNIQUES; REGRESSION TREE MODELS; REGRESSION TREES; RESEARCH AND ANALYSIS;

DATA PRIVACY;

EID: 84944877196     PISSN: 02767783     EISSN: 21629730     Source Type: Journal    
DOI: 10.25300/MISQ/2014/38.3.03     Document Type: Article

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