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SUMMARY:Privacy preserving data mining in distributed databases - Ehud Gud
 es\, Department of Computer Science\, Ben-Gurion University
DTSTART:20060926T151500Z
DTEND:20060926T161500Z
UID:TALK5376@talks.cam.ac.uk
CONTACT:Saar Drimer
DESCRIPTION:Privacy concerns have become an important issue in Data Mining
 . This seminar deals with the problem of association rule mining from dist
 ributed vertically partitioned data with the goal of preserving the confid
 entiality of each database. Each site holds some attributes of each transa
 ction\, and the sites wish to work together to find globally valid associa
 tion rules without revealing individual transaction data. This problem occ
 urs\, for example\, when the same users access several electronic shops pu
 rchasing different items in each\, and the shops like to cooperate to obta
 in valid global rules without compromising their private databases.\n\nIn 
 this talk\, we first review the work on privacy based rules mining in both
  centralized and distributed databases\, and in both vertically and horizo
 ntally pertitioned databases. We then present two algorithms for discoveri
 ng frequent item sets and two algorithms for extracting the association ru
 les. We analyze the security\, privacy and complexity properties of the al
 gorithms and compare them to the best known algorithms of Vaidya and Clift
 on.
LOCATION:Lecture Theatre 2\, Computer Laboratory\, William Gates Building
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