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Private Over-Threshold Aggregation Protocols over Distributed Datasets

delete2016-09-01
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PRE
AI
M
Myungsun Kim *
A
Aziz Mohaisen
J
Jung Hee Cheon
Y
Yongdae Kim
DOI:10.1109/TKDE.2016.2572686delete
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Abstract

Abstract

En 中文
In this paper, we revisit the private over-threshold data aggregation problem. We formally define the problem's security requirements as both data and user privacy goals. To achieve both goals, and to strike a balance between efficiency and functionality, we devise an efficient cryptographic construction and its proxy-based variant. Both schemes are provably secure in the semi-honest model. Our key idea for the constructions and their malicious variants is to compose two encryption functions tightly coupled in a way that the two functions are commutative and one public-key encryption has an additive homomorphism. We call that double encryption. We analyze the computational and communication complexities of our construction, and show that it is much more efficient than the existing protocols in the literature. Specifically, our protocol has linear complexity in computation and communication with respect to the number of users. Its round complexity is also linear in the number of users. Finally, we show that our basic protocol is efficiently transformed into a stronger protocol secure in the presence of malicious adversaries, and provide the resulting protocol's performance and security analysis.
Keywords:
Network traffic distribution
data aggregation
privacy preservation
malicious security
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Journal

IEEE Transactions on Knowledge and Data Engineering cover
IEEE Transactions on Knowledge and Data Engineering
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state university of new york (suny) system
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university at buffalo, suny
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suwon university
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seoul national university (snu)
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Citations: 86
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