云计算中基于用户行为和推荐的信任计算框架

T. Mujawar, L. B. Bhajantri
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引用次数: 0

摘要

云计算为用户随时随地可用的不同资源和服务提供共享环境。云计算已经引起了用户和企业的广泛关注。然而,安全问题是接受云计算的主要障碍之一。为了保证数据的安全性,有必要将数据的访问权限授予授权用户。传统的系统在授予任何用户访问权限时,采用不同的访问策略和权限。用户行为分析也是一个重要方面,可以将其集成到访问控制模型中。本文在提供对云数据的访问时,提出了考虑用户行为的信任计算模型。对用户的推荐也是评估用户行为的重要组成部分之一。该模型基于信誉和推荐对用户的可信度进行评估。随着机器学习技术的出现,基于学习的技术在安全领域的应用得到了广泛的应用。该方法将机器学习技术(k-means聚类算法)引入到信任计算过程中,并根据用户的信任值对用户进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trust Computation Framework based on User Behavior and Recommendation in Cloud Computing
Cloud computing provides shared environment for different resources and services that are available for users at anytime and from anywhere. Cloud computing has gained considerable attention of users and businesses. However, security concern is one of the major hurdles for acceptance of cloud computing. In order to guarantee security of data, it is necessary to grant access of data, only to authorized users. The traditional system applies different access policies and permission while granting access to any user. The analysis of user behavior is also important aspect, which can be integrated into access control model. In this paper, the trust computation model is presented that takes user behavior into consideration while providing access to the cloud data. The recommendation for the user is also one of the important components to assess user behavior. The proposed model evaluates trustworthiness of user on basis of reputation and recommendation. With the advent in machine learning techniques, applying learning based techniques in security domain has gained lots of popularity. In the proposed method, the machine learning technique (k-means clustering Algorithm) is incorporated in the trust computation process and the users are classified according their trust values.
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