Title
A Framework for Detecting Malware in Cloud by Identifying Symptoms
Abstract
Security is seen as one of the major challenges of the Cloud computing. Recent malware are not only becoming more sophisticated, but have also demonstrated a trend to make use of components, which can easily be distributed through the Internet to develop newer and better malware. As a result, the key problem facing Cloud security is to cope with identifying diverse sets of malware. This paper presents a method of detecting malware by identifying the symptoms of malicious behaviour as opposed to looking for the malware itself. This can be compared to the use of symptoms in human pathology, in which study of symptoms direct physicians to diagnosis of a disease or possible causes of illnesses. The main advantage of shifting the attention to the symptoms is that a wide range of malicious behaviour can result in the same set of symptoms. We propose the creation of Forensic Virtual Machines (FVM), which are mini Virtual Machines (VM) that can monitor other VMs to discover the symptoms. In this paper, we shall present a framework to support the FVMs so that they collaborate with each other in identifying symptoms by exchanging messages via secure channels. The FVMs report to a Command & Control module that collects and correlates the information so that suitable remedial actions can take place in real-time. The Command & Control can be compared to the physician who infers possibility of an illness from the occurring symptoms. In addition, as FVMs make use of the computational resources of the system we will present an algorithm for sharing of the FVMs so that they can be guided to search for the symptoms in the VMs with higher priority.
Year
DOI
Venue
2012
10.1109/EDOC.2012.27
EDOC
Keywords
Field
DocType
mini virtual machines,control module,detecting malware,cloud security,better malware,fvms report,symptoms direct physician,malicious behaviour,cloud computing,identifying symptoms,forensic virtual machines,recent malware,algorithm design and analysis,cloud,virtual machines,malware,linux,virtualisation,security
Virtualization,Data mining,Virtual machine,Algorithm design,Computer security,Computer science,Software,Cloud computing security,Malware,The Internet,Cloud computing
Conference
ISSN
Citations 
PageRank 
2325-6354
14
0.77
References 
Authors
8
5
Name
Order
Citations
PageRank
Keith Harrison1171.56
Behzad Bordbar271452.94
Syed T. T. Ali3140.77
Chris I. Dalton414315.21
Andrew Norman5140.77