Multi-party, privacy-preserving distributed data mining using a game theoretic framework

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4702 LNAI, Issue , 2007, Pages 523-531

  Kargupta, Hillol ^a,c   Das, Kamalika ^a   Liu, Kun ^b  

^a UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

^b IBM ALMADEN RESEARCH CENTER   (United States)

^c AGNIK LLC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; GAME THEORY; NETWORK PROTOCOLS; SECURITY OF DATA; SENSITIVITY ANALYSIS;

MULTI-PARTY GAME; PRIVACY-PRESERVING DISTRIBUTED DATA MINING (PPDM); SENSITIVE DATA; SUM COMPUTATION;

DATA MINING;

EID: 38049134850     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74976-9_54     Document Type: Conference Paper

References (8)

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