A privacy preserving technique for distance-based classification with worst case privacy guarantees

Data and Knowledge Engineering

Volumn 66, Issue 2, 2008, Pages 264-288

  Mukherjee, Shibnath ^a   Banerjee, Madhushri ^a   Chen, Zhiyuan ^a   Gangopadhyay, Aryya ^a  

^a UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

Author keywords

Data mining; K nearest neighbor classification; Privacy preserving data mining; Security and privacy

Indexed keywords

ACOUSTIC NOISE; ADMINISTRATIVE DATA PROCESSING; ALGORITHMS; CANNING; CLASSIFICATION (OF INFORMATION); CORRELATION METHODS; DEMODULATION; ECHO SUPPRESSION; ELECTRIC BREAKDOWN; EVOLUTIONARY ALGORITHMS; FINANCIAL DATA PROCESSING; FOOD ADDITIVES; KETONES; LAPLACE TRANSFORMS; MATHEMATICAL TRANSFORMATIONS; MINING; PERTURBATION TECHNIQUES;

(I ,J) CONDITIONS; AVERAGE-CASE; DATA CORRELATIONS; DISTANCE BASED; DISTANCE BASED CLASSIFICATION; DISTORTION (DEFORMATION); ELSEVIER (CO); K-NEAREST NEIGHBOR CLASSIFICATION; LAPLACE NOISE; MINING ALGORITHMS; ORTHOGONAL TRANSFORMS; PCA TRANSFORM; PERTURBATION METHODS; PRINCIPAL COMPONENTS; PRIVACY PRESERVING; PRIVACY PROTECTION; RANDOM PROJECTIONS; SANITIZATION; WORST CASE;

PRINCIPAL COMPONENT ANALYSIS;

EID: 45249117455     PISSN: 0169023X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.datak.2008.03.004     Document Type: Article

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