Development of Digital Forensic Framework for Joint Heterogeneous Cloud Computing Platforms

Abstract

Introduction Cloud computing technology renders the acquisition of hardware and software by the industrial institutions and academic institutions useless, as sensitive data or information are often stored in cloud service provider's data centers around the globe not on institutions local disk drives anymore. Different cloud platforms such as OpenStack, Amazon Web Service (AWS), Rackspace, Google Compute Engine (GCE) and Microsoft Azure and others, provide services to cloud-end users on a pay-as-you-go service, the users only pay cloud resources utilised(Sotiriadis & Bessis, 2015). Today, various Cloud Service Providers (CSP) aimed to interoperable clouds. The effort is to join different forms of cloud service providers, aggregated to one cloud platform(Yu, Stella, & Schueller, 2014). Some scholars also indicated broad interest in creating a cloud-of-clouds where multiple cloud service providers can gain access of resources of each other seamlessly, which we and others call the multi-cloud(Smit, Simmons, & Litoiu, 2013). The main issues with joining multiple and different configured cloud service providers are most of the cloud systems are not compatible with one another and cannot share services with other, since everyone speaks a different language(Garrison, 2010). There are no service standards that are specific to that effort of joining two or more clouds, and these standards are deployed on web browser interfaces. Some of the cloud providers use SOAP; other ones use REST as communication protocols. Each service has its specific characteristics such as authentication and security requirements(Elhozmari& Ettalbi, 2016). Cloud service providers have not taken into consideration Cloud interoperability issues and each Cloud comes with its service and interfaces for services (Toosi, Calheiros, & Buyya, 2014). Inconsistency in log formats and data representations with an individual cloud to other clouds, present challenges to a digital investigator, who needs to capture the meaning of the various fields of data in each log to perform a thorough analysis(Kent & Souppaya, 2006). "The failure of one operating system logging format to be accepted to the other logging format of operating system creates incompatibility and heterogeneity with the logging functions within clouds operating systems or network devices. This makes centralizing logging is a challenging task"(Sahoo& Chottray, 2012). With the development of this new technology of joining multiple clouds to interoperate and derive other benefits of interconnections, the intruders get unauthorized access to some resources on cloud computing servers with a malicious ego to steal services or gain access to some vital information. For example, cybercriminals are utilising existing cloud services as their infrastructure to target their victims(Alqahtany, Clarke, Furnell, & Reich, 2016). To assist in detecting malicious users and in analysing the giant clouds logs, mega clouds organisations need to deploy automated methods of converting logs with different content and fo...

Characterizing the architectures and brokering protocols for enabling clouds interconnection

“…The research carried out in Reference 57 to interconnect the multiple clouds is based on metabrokering components, which is novel approach inspired from the metacomputing and scheduling, enabling the collaboration to realize the interoperability among heterogeneous clouds. 58 Metabrokering components are bare-bones that function in decentralized manner and provide the interface to clients for applications submission. The role of these components in this architecture is to provide high-level brokering while coordinating with local-brokers.…”