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ABSTRACT
Du, Wenliang. Ph.D., Purdue University, August, 2001. A Study of Several Speci c
Secure Two-party Computation Problems. Major Professors: Mikhail J. Atallah
and Eugene H. Spa ord.
Alice has a private input x (of any data type, such as a number, a matrix or a
data set). Bob has another private input y. Alice and Bob want to cooperatively
conduct a speci c computation on x and y without disclosing to the other person any
information about her or his private input except for what could be derived from the
results. This problem is a Secure Two-party Computation (STC) problem, which has
been extensively studied in the past. Several generic solutions have been proposed to
solve the general STC problem; however the generic solutions are often too ineÆcient
to be practical. Therefore, in this dissertation, we study several speci c STC problems
with the goal of nding more eÆcient solutions than the generic ones.
We introduce a number of speci c STC problems in the domains of scienti c
computation, statistical analysis, computational geometry and database query. Most
of the problems have not been studied before in the literature.
To solve these problems:
 We investigate how data perturbation could be used to hide data. Data pertur-
bation hides a datum by adding to it a random number. We show that this
technique is e ective in preserving privacy.
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 We explore how domain speci c knowledge can improve the eÆciency of the
solutions that we develop over the generic solutions that do not consider domain
speci c knowledge. We show that such knowledge is important in both hiding
data and achieving higher eÆciency.
 We also introduce a number of common building blocks that are useful in solving
secure two-party computation problems in various computation domains.

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