AC-Framework for Privacy-Preserving Collaboration

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Author

Christopher Clifton

Tech report number

CERIAS TR 2007-100

Entry type

conference

Abstract

The secure multi-party computation (SMC) model provides means for balancing the use and confidentiality of distributed data. Increasing security concerns have led to a surge in work on practical secure multi- party computation protocols. However, most are only proven secure under the semi-honest model, and security under this adversary model is insufficient for most applications. In this paper, we propose a novel framework: accountable computing (AC) framework, which is sufficient or practical for many applications without the complexity and cost of a SMC-protocol under the malicious model. Furthermore, to show the applicability of the AC-framework, we present an application under this framework regarding privacy-preserving mining frequent itemsets.

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Date

2007 – 04

URL

http://www.cs.purdue.edu/homes/wjiang/AC-Framework.pdf

Key alpha

Clifton

Note

2007 SIAM International Conference on Data Mining (SDM07) April 26-28, 2007 in Minneapolis, Minnesota

Publication Date

2007-04-01

BibTex-formatted data

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@Conference{ Clifton,
	title = "AC-Framework for Privacy-Preserving Collaboration",
	author = "Christopher Clifton",
	year = "2007",
	month = "04",
	note = "2007 SIAM International Conference on Data Mining (SDM07)
April 26-28, 2007 in Minneapolis, Minnesota",
	abstract = "The secure multi-party computation (SMC) model provides means for balancing the use and confidentiality of distributed data. Increasing security concerns have led to a surge in work on practical secure multi- party computation protocols. However, most are only proven secure under the semi-honest model, and security under this adversary model is insufficient for most applications. In this paper, we propose a novel framework: accountable computing (AC)
framework, which is sufficient or practical for many applications without the complexity and
cost of a SMC-protocol under the malicious model. Furthermore, to show the applicability of the AC-framework, we present an application under this framework regarding privacy-preserving
mining frequent itemsets.",
	url = "http://www.cs.purdue.edu/homes/wjiang/AC-Framework.pdf",
}