TY - GEN
T1 - Private multiparty sampling and approximation of vector combinations
AU - Ishai, Yuval
AU - Malkin, Tal
AU - Strauss, Martin J.
AU - Wright, Rebecca N.
PY - 2007
Y1 - 2007
N2 - We consider the problem of private efficient data mining of vertically-partitioned databases. Each of several parties holds a column of a data matrix (a vector) and the parties want to investigate the componentwise combination of their vectors. The parties want to minimize communication and local computation while guaranteeing privacy in the sense that no party learns more than necessary. Sublinear-communication private protocols have been primarily been studied only in the two-party case. We give efficient multiparty protocols for sampling a row of the data matrix and for computing arbitrary functions of a row, where the row index is additively shared among two or more parties. We also give protocols for approximating the componentwise sum, minimum, or maximum of the columns in which the communication and the number of public-key operations are at most polynomial in the size of the small approximation and polylogarithmic in the number of rows.
AB - We consider the problem of private efficient data mining of vertically-partitioned databases. Each of several parties holds a column of a data matrix (a vector) and the parties want to investigate the componentwise combination of their vectors. The parties want to minimize communication and local computation while guaranteeing privacy in the sense that no party learns more than necessary. Sublinear-communication private protocols have been primarily been studied only in the two-party case. We give efficient multiparty protocols for sampling a row of the data matrix and for computing arbitrary functions of a row, where the row index is additively shared among two or more parties. We also give protocols for approximating the componentwise sum, minimum, or maximum of the columns in which the communication and the number of public-key operations are at most polynomial in the size of the small approximation and polylogarithmic in the number of rows.
UR - http://www.scopus.com/inward/record.url?scp=38149075945&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-73420-8_23
DO - 10.1007/978-3-540-73420-8_23
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AN - SCOPUS:38149075945
SN - 3540734198
SN - 9783540734192
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 243
EP - 254
BT - Automata, Languages and Programming - 34th International Colloquium, ICALP 2007, Proceedings
T2 - 34th International Colloquium on Automata, Languages and Programming, ICALP 2007
Y2 - 9 July 2007 through 13 July 2007
ER -