NDLI: Computing multi-party trust privately: in O(n) time units sending one (possibly large) message at a time

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Feature interaction networks

Computing multi-party trust privately: in O(n) time units sending one (possibly large) message at a time

Content Provider	ACM Digital Library
Author	Kopeetsky, Marina Dolev, Shlomi Gilboa, Niv
Abstract	Schemes for multi-party trust computation are presented. The schemes do not make use of a Trusted Authority. The schemes are more efficient than previous schemes by the number of messages exchanged which is proportional to the number of participants rather than to a quadratic number of the participants. We note that in our schemes the length of each message may be larger than the message length of previous schemes. The calculation of a trust, in a specific user by a group of community members, starts upon a request of an initiating user. The trust computation is provided in a completely distributed manner, while each user calculates its trust value privately. Given a community C and its members (users) $U_{1},$ ., $U_{n},$ we present computationally secure schemes for trust computation. The first Accumulated Protocol AP computes the average trust in a specific user $U_{t}$ upon the trust evaluation request initiated by a user $U_{n}.$ The exact trust values of each queried user are not disclosed to $U_{n}.$ The next Weighted Accumulated protocol WAP generates the average weighted trust in a specific user $U_{t}$ taking into consideration the unrevealed trust that $U_{n}$ has in each user participating in the trust process evaluation. We extend our schemes to the case when the initiating user $U_{n}$ can be compromised by the adversary, and we introduce the Multiple Private Keys M P K P and the Multiple Private Keys Weighted M P W P protocols for computing average unweighted and weighted trust, respectively. The computation of all our algorithms requires the transmission of O(n) (possibly large) messages.
Starting Page	1460
Ending Page	1465
Page Count	6
File Format	PDF
ISBN	9781605586397
DOI	10.1145/1774088.1774401
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-03-22
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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