Classifying and Filtering Users by Similarity Measures for Trust Management in Cloud Environment
Author(s) -
Fatima Zohra Filali,
Belabbas Yagoubi
Publication year - 2015
Publication title -
scalable computing practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.192
H-Index - 18
ISSN - 1895-1767
DOI - 10.12694/scpe.v16i3.1102
Subject(s) - computer science , cloud computing , process (computing) , similarity (geometry) , order (exchange) , collaborative filtering , cluster analysis , data mining , computer security , recommender system , information retrieval , machine learning , artificial intelligence , business , finance , image (mathematics) , operating system
Trust represents an important issue for adopting cloud services. A trust management framework is essentially, about user rating. Hence, correctly addressing user feedback and filtering out malicious rating is a main step in providing reliable services. In order to process their feedback and calculate a reliable trust degree. Thus, new opportunities can be offered for the establishment of a trust relationship among involved entities. We propose a technique to process user rating by statistical methods. Then, we proceed to classify the users into different groups to detect malicious users. The users are grouped according to their rating by a k-means clustering technique, and the evaluation will show that the proposed solution gives better results than the traditional filtering solution.
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