Privacy-Preserving Set Operations

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 privacy-preserving 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 privacy-preserving 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. This research was supported in part by the Center for Computer and Communications Security at Carnegie Mellon under grant DAAD19-02-1-0389 from the Army Research Office. ...

• Type: Conference
• Year: 2005
• Where: CRYPTO
• Authors: Lea Kissner, Dawn Xiaodong Song
• Keywords: CRYPTO 2005, Private Input, Private Input Multiset, Private Input Sets