Intrusion Detection by Forensic Method in Private Cloud using Eucalyptus

Abstract

Cloud computing has become the mature term which has dealt from single user to large enterprises. The private cloud platform building framework Eucalyptus has great pace of development within short span of time. Achieving AWS (Amazon Web Services) compatible features development along with scalability and sustainability has introduced several issues have an adverse effect on the cloud system. In continuing with this, the chances of intrusion also increase evading traditional mechanism of security. Issues have been introduced due to seamless integration of such structure with computing technologies and so on. By taking advantage of such flaws, the Cybercrime is rapidly increasing in this field. The proposed work is regarded with Digital forensics technique and intrusion detection mechanism. In this scope of work, an experimental setup of Eucalyptus with Snort NIDS (Network Intrusion Detection System) to detect attacks using snort rules has been created. The Eucalyptus Cloud components and Snort logs are exported to outside cloud network to rSyslog server which would be later analyzed by the Awstats log analyzer. Accompanied to above, this scope of work also addresses toward the issue of Eucalyptus to export its logs to the remote rSyslog server. This system will definitely help to reduce the strain on the Cloud forensics.

Secure logging scheme for forensic analysis in cloud

“…According to the survey report of Gartner, the increasing usage of cloud services brings the annual revenue of $216 billion in 2020 . This increasing usage of cloud services motivates the attackers to send enormous malicious requests to the victim Virtual Machine (VM) instances, thereby exhausting all the resources of the victim . If any of the VMs in the cloud is vulnerable to Denial of Service (DoS) attack, then the entire infrastructure can also be compromised.…”