Title
Reputation Evaluation with Malicious Feedback Prevention Using a HITS-Based Model
Abstract
The reputation of web services is calculated by aggregating user feedback ratings. Though reputation is a subjective metric, it can be considered as a good indicator about service's Quality of Experience, and henceforth, it can be used for recommending services in an open ecosystem. In this work, we propose a three-phase process for evaluating web service reputation by aggregating user feedback ratings. The relationship between users and services is modeled as a bi-partite graph where an adapted HITS (Hypertext Induced Topic Search) algorithm is employed to distinguish between honest and malicious users in Phase I. Then, this model is used to evaluate, in Phase III, the reputation of web services from user ratings after punishing malicious users in Phase II. An experiment on a dataset of real Web services was conducted to validate the effectiveness of the proposed model in evaluating Web service reputation.
Year
DOI
Venue
2019
10.1109/ICWS.2019.00039
2019 IEEE International Conference on Web Services (ICWS)
Keywords
Field
DocType
Web services,Reputation,HITS algorithm,User credibility evaluation
Hypertext,Graph,World Wide Web,HITS algorithm,Computer science,Quality of experience,Web service,Database,Reputation
Conference
ISBN
Citations 
PageRank 
978-1-7281-2718-7
1
0.36
References 
Authors
15
3
Name
Order
Citations
PageRank
Okba Tibermacine1111.89
Chouki Tibermacine217924.16
Mohamed Lamine Kerdoudi310.36