Private Information Retrieval

Private Information Retrieval (1997)

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by Benny Chor , Oded Goldreich , Eyal Kushilevitz , Madhu Sudan

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Datum	Value	Source
TITLE	Private Information Retrieval	user correction
AUTHOR NAME	Benny Chor	user correction
AUTHOR NAME	Oded Goldreich	user correction
AUTHOR AFFIL	Computer Science and Applied Math. Dept., Weizmann Institute of Science	user correction
AUTHOR ADDR	Rehovot, Israel	user correction
AUTHOR NAME	Eyal Kushilevitz	user correction
AUTHOR NAME	Madhu Sudan	user correction
AUTHOR AFFIL	IBM Research Division, T.J. Watson Research Center	user correction
AUTHOR ADDR	P.O. Box 218, Yorktown Heights, NY 10598	user correction
ABSTRACT	Publicly accessible databases are an indispensable resource for retrieving up to date information. But they also pose a significant risk to the privacy of the user, since a curious database operator can follow the user's queries and infer what the user is after. Indeed, in cases where the users ' intentions are to be kept secret, users are often cautious about accessing the database. It can be shown that when accessing a single database, to completely guarantee the privacy of the user, the whole database should be downloaded, namely n bits should be communicated (where n is the number of bits in the database). In this work, we investigate whether by replicating the database, more efficient solutions to the private retrieval problem can be obtained. We describe schemes that enable a user to access k replicated copies of a database (k * 2) and privately retrieve information stored in the database. This means that each individual database gets no information on the identity of the item retrieved by the user. Our schemes use the replication to gain substantial saving. In particular, we have ffl A two database scheme with communication complexity of O(n1=3). ffl A scheme for a constant number, k, of databases with communication complexity O(n1=k). ffl A scheme for 13 log2 n databases with polylogarithmic (in n) communication complexity.	user correction
YEAR	1997	SVM HeaderParse 0.2
CITATIONS	15 found	ParsCit 1.0