A Multi-scenario Reputation Estimation Framework and its Resilience Study against Various forms of Attacks
Khan, J.I.
Shaikh, S.S.
MediaKent State Univ., Kent;
This paper appears in: Web Intelligence, IEEE/WIC/ACM International Conference on
Publication Date: 2-5 Nov. 2007
On page(s): 676-682
Location: Fremont, CA,
ISBN: 978-0-7695-3026-0
INSPEC Accession Number: 9894841
Digital Object Identifier: 10.1109/WI.2007.134
Current Version Published: 2008-01-07
Abstract
Online transactional activities that involve establishment of trust between participating individual seem to require a reputation function for the reputation estimation framework (REF). They are often vulnerable to various kinds of attacks. Also it seems we do not evaluate reputation in the same way in all situations. Using Occam's razor we propose a generalized set-theoretic reputation function with customizable components that can be changed to meet the reputation requirements in wide variety of reputation assessment scenarios. Further we identify several canonical classes of the functions. The resilience of the framework is then analyzed by subjecting it to various reputation attacks such as gang attacks, vendetta and Dr Jekyll & Mr. Hyde.
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