Privacy preserving framework for brute force attacks in cloud environment Online publication date: Mon, 13-Mar-2017
by Ambika Vishal Pawar; Ajay R. Dani
International Journal of High Performance Computing and Networking (IJHPCN), Vol. 10, No. 1/2, 2017
Abstract: Cloud model of computing will be widely adopted by different organisations if it can support a higher level of data privacy than currently supported. The higher level of data privacy is mandatory to store and query the sensitive data in cloud-based information system applications such as customer relationship management (CRM) systems. Identity-based homomorphic encryption and tokenisation has proved its efficiency in providing privacy and simultaneously querying encrypted data. However, in cloud-based software-as-a-service (SaaS) model, the adversary can run brute force attacks which can reveal the attribute values by colluding with the service provider. It is a significant challenge to detect and prevent such attacks. This paper presents a comprehensive solution using application-independent metrics consisting of different types of vulnerability measures. This paper also presents the detailed design of a system that uses application-independent metrics to prevent brute force attacks.
Online publication date: Mon, 13-Mar-2017
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of High Performance Computing and Networking (IJHPCN):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com