Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Collaborative Intrusion Detection in Federated Cloud Environments

Mac Dermott, AM and Shi, Q and Kifayat, K (2015) Collaborative Intrusion Detection in Federated Cloud Environments. Journal of Computer Sciences and Applications, 3 (3A). pp. 10-20. ISSN 2328-7268

[img] Text
Aine MacDermott Final.pdf - Accepted Version
Available under License Creative Commons Attribution.

Download (656kB)

Abstract

Moving services to the Cloud is a trend that has steadily gained popularity over recent years, with a constant increase in sophistication and complexity of such services. Today, critical infrastructure operators are considering moving their services and data to the Cloud. Infrastructure vendors will inevitably take advantage of the benefits Cloud Computing has to offer. As Cloud Computing grows in popularity, new models are deployed to exploit even further its full capacity, one of which is the deployment of Cloud federations. A Cloud federation is an association among different Cloud Service Providers (CSPs) with the goal of sharing resources and data. In providing a larger-scale and higher performance infrastructure, federation enables on-demand provisioning of complex services. In this paper we convey our contribution to this area by outlining our proposed methodology that develops a robust collaborative intrusion detection methodology in a federated Cloud environment. For collaborative intrusion detection we use the Dempster-Shafer theory of evidence to fuse the beliefs provided by the monitoring entities, taking the final decision regarding a possible attack. Protecting the federated Cloud against cyber attacks is a vital concern, due to the potential for significant economic consequences.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science
Publisher: Science and Education Publishing
Date Deposited: 15 Aug 2017 09:33
Last Modified: 07 Sep 2017 09:05
DOI or Identification number: 10.12691/jcsa-3-3A-2
URI: http://researchonline.ljmu.ac.uk/id/eprint/6936

Actions (login required)

View Item View Item