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Privacy Preserving Data Mining
 JOURNAL OF CRYPTOLOGY
, 2000
"... In this paper we address the issue of privacy preserving data mining. Specifically, we consider a scenario in which two parties owning confidential databases wish to run a data mining algorithm on the union of their databases, without revealing any unnecessary information. Our work is motivated b ..."
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Cited by 525 (9 self)
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In this paper we address the issue of privacy preserving data mining. Specifically, we consider a scenario in which two parties owning confidential databases wish to run a data mining algorithm on the union of their databases, without revealing any unnecessary information. Our work is motivated by the need to both protect privileged information and enable its use for research or other purposes. The
Privacypreserving set operations
 in Advances in Cryptology  CRYPTO 2005, LNCS
, 2005
"... In many important applications, a collection of mutually distrustful parties must perform private computation over multisets. Each party’s input to the function is his private input multiset. In order to protect these private sets, the players perform privacypreserving computation; that is, no part ..."
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Cited by 161 (0 self)
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In many important applications, a collection of mutually distrustful parties must perform private computation over multisets. Each party’s input to the function is his private input multiset. In order to protect these private sets, the players perform privacypreserving computation; that is, no party learns more information about other parties ’ private input sets than what can be deduced from the result. In this paper, we propose efficient techniques for privacypreserving operations on multisets. By employing the mathematical properties of polynomials, we build a framework of efficient, secure, and composable multiset operations: the union, intersection, and element reduction operations. We apply these techniques to a wide range of practical problems, achieving more efficient results than those of previous work.
Secure Multiparty Computation for PrivacyPreserving Data Mining
, 2008
"... In this paper, we survey the basic paradigms and notions of secure multiparty computation and discuss their relevance to the field of privacypreserving data mining. In addition to reviewing definitions and constructions for secure multiparty computation, we discuss the issue of efficiency and demon ..."
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Cited by 92 (0 self)
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In this paper, we survey the basic paradigms and notions of secure multiparty computation and discuss their relevance to the field of privacypreserving data mining. In addition to reviewing definitions and constructions for secure multiparty computation, we discuss the issue of efficiency and demonstrate the difficulties involved in constructing highly efficient protocols. We also present common errors that are prevalent in the literature when secure multiparty computation techniques are applied to privacypreserving data mining. Finally, we discuss the relationship between secure multiparty computation and privacypreserving data mining, and show which problems it solves and which problems it does not. 1
Cryptographic Techniques for PrivacyPreserving Data Mining
 SIGKDD Explorations
, 2002
"... Research in secure distributed computation, which was done as part of a larger body of research in the theory of cryptography, has achieved remarkable results. It was shown that nontrusting parties can jointly compute functions of their different inputs while ensuring that no party learns anything ..."
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Cited by 92 (0 self)
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Research in secure distributed computation, which was done as part of a larger body of research in the theory of cryptography, has achieved remarkable results. It was shown that nontrusting parties can jointly compute functions of their different inputs while ensuring that no party learns anything but the defined output of the function. These results were shown using generic constructions that can be applied to any function that has an ecient representation as a circuit. We describe these results, discuss their efficiency, and demonstrate their relevance to privacy preserving computation of data mining algorithms. We also show examples of secure computation of data mining algorithms that use these generic constructions.
Parallel CoinTossing and ConstantRound Secure TwoParty Computation
 Journal of Cryptology
, 2001
"... Abstract. In this paper we show that any twoparty functionality can be securely computed in a constant number of rounds, where security is obtained against malicious adversaries that may arbitrarily deviate from the protocol specification. This is in contrast to Yao’s constantround protocol that e ..."
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Cited by 76 (13 self)
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Abstract. In this paper we show that any twoparty functionality can be securely computed in a constant number of rounds, where security is obtained against malicious adversaries that may arbitrarily deviate from the protocol specification. This is in contrast to Yao’s constantround protocol that ensures security only in the face of semihonest adversaries, and to its malicious adversary version that requires a polynomial number of rounds. In order to obtain our result, we present a constantround protocol for secure cointossing of polynomially many coins (in parallel). We then show how this protocol can be used in conjunction with other existing constructions in order to obtain a constantround protocol for securely computing any twoparty functionality. On the subject of cointossing, we also present a constantround perfect cointossing protocol, where by “perfect ” we mean that the resulting coins are guaranteed to be statistically close to uniform (and not just pseudorandom). 1
Secure multiparty computational geometry
 INTERNATIONAL WORKSHOP ON ALGORITHMS AND DATA STRUCTURES
, 2001
"... The general secure multiparty computation problem is when multiple parties (say, Alice and Bob) each have private data (respectively, a and b) and seek to compute some function f(a; b) without revealing to each other anything unintended (i.e., anything other than what can be inferred from knowing f ..."
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Cited by 67 (9 self)
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The general secure multiparty computation problem is when multiple parties (say, Alice and Bob) each have private data (respectively, a and b) and seek to compute some function f(a; b) without revealing to each other anything unintended (i.e., anything other than what can be inferred from knowing f(a; b)). It is well known that, in theory, the general secure multiparty computation problem is solvable using circuit evaluation protocols. While this approach is appealing in its generality, the communication complexity of the resulting protocols depend on the size of the circuit that expresses the functionality to be computed. As Goldreich has recently pointed out [6], using the solutions derived from these general results to solve specic problems can be impractical; problemspeci c solutions should be developed, for eciency reasons. This paper is a rst step in this direction for the area of computational geometry. We give simple solutions to some specic geometric problems, and in doing so we develop some building blocks that we believe will be useful in the solution of other geometric and combinatorial problems as well.
Location privacy via private proximity testing
 In NDSS
, 2011
"... We study privacypreserving tests for proximity: Alice can test if she is close to Bob without either party revealing any other information about their location. We describe several secure protocols that support private proximity testing at various levels of granularity. We study the use of “locatio ..."
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Cited by 53 (1 self)
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We study privacypreserving tests for proximity: Alice can test if she is close to Bob without either party revealing any other information about their location. We describe several secure protocols that support private proximity testing at various levels of granularity. We study the use of “location tags ” generated from the physical environment in order to strengthen the security of proximity testing. We implemented our system on the Android platform and report on its effectiveness. Our system uses a social network (Facebook) to manage user public keys. 1
Efficient robust private set intersection
 IN: ACNS
, 2009
"... Computing Set Intersection privately and efficiently between two mutually mistrusting parties is an important basic procedure in the area of private data mining. Assuring robustness, namely, coping with potentially arbitrarily misbehaving (i.e., malicious) parties, while retaining protocol efficien ..."
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Cited by 46 (1 self)
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Computing Set Intersection privately and efficiently between two mutually mistrusting parties is an important basic procedure in the area of private data mining. Assuring robustness, namely, coping with potentially arbitrarily misbehaving (i.e., malicious) parties, while retaining protocol efficiency (rather than employing costly generic techniques) is an open problem. In this work the first solution to this problem is presented.
Enhancing Privacy and Trust in Electronic Communities
 In Proc. of the 1st ACM Conference on Electronic Commerce
, 1999
"... A major impediment to using recommendation systems and collective knowledge for electronic commerce is the reluctance of individuals to reveal preferences in order to find groups of people that share them. An equally important barrier to fluid electronic commerce is the lack of agreed upon trusted t ..."
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Cited by 44 (4 self)
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A major impediment to using recommendation systems and collective knowledge for electronic commerce is the reluctance of individuals to reveal preferences in order to find groups of people that share them. An equally important barrier to fluid electronic commerce is the lack of agreed upon trusted third parties. We propose new nonthird party mechanisms to overcome these barriers. Our solutions facilitate finding shared preferences, discovering communities with shared values, removing disincentives posed by liabilities, and negotiating on behalf of a group. We adapt known techniques from the cryptographic literature to enable these new capabilities. 1 Introduction With the advent of the World Wide Web and the ease of entry enabled by the Internet, electronic commerce is becoming an increasing reality, with a consequent growth in the number and variety of information providers and ecommerce sites. While this growth generates a diverse set of offerings from which consumers can only be...