Peer-to-peer secure multi-party numerical computation facing malicious adversaries-Reference-Cited by-同舟云学术

Peer-to-peer secure multi-party numerical computation facing malicious adversaries

Published:2009-06-10 Issue:2 Volume:3 Page:129-144
ISSN:1936-6442
Container-title:Peer-to-Peer Networking and Applications
language:en
Short-container-title:Peer-to-Peer Netw. Appl.

Author:

Bickson Danny,Reinman Tzachy,Dolev Danny,Pinkas Benny

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Link

http://link.springer.com/content/pdf/10.1007/s12083-009-0051-9.pdf

Reference35 articles.

1. GMP (2009) The GNU MP Bignum library. http://gmplib.org

2. Netflix (2009) Netflix homepage. www.netflix.org

3. Advanced Crypto Software Collection (2006) Paillier C implementation by John Bethencourt. http://acsc.csl.sri.com/libpaillier/

4. Agrawal R, Srikant R (2000) Privacy-preserving data mining. In: Proceedings of the 2000 ACM SIGMOD international conference on management of data, ACM, Dallas, 16–18 May 2000, pp 439–450

5. Anker T, Bickson D, Dolev D, Hod B (2008) Efficient clustering for improving network performance in wireless sensor networks. In: European conference on wireless sensor networks (EWSN’08)

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