This study aimed at modelling the daily Naira/Pound exchange rate volatility with ARIMA and GARCH type models with daily exchange rate ranging from June 2016 to July 2019 is obtained from Central Bank of Nigeria. The stationarity of the data series was checked using graphical analysis, Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) tests, it was found out that the exchange rate series is not stationary, the return of the series was obtained and found out to be stationary. It was observed that ARIMA (2, 1, 1) and GARCH (1,1) are the optimal with the highest log-likelihood and lowest AIC and BIC.
The cloud computing is nowadays an embracing computing technology by many organizations, academic institutions and business centers. Resources availability, resources capacity, security are among the factors that subscriber consider while rating Cloud Service Providers when subscribing. Cloud Service Providers (CSPs) are limited in some resources, lacking some resources requested by their customers, this gave rise to the need for interconnecting multiple clouds to interoperate and share resources. The interconnected clouds can be in different features and schemes and the system can be prone to insecurity or intrusion. The architectural modeling system was used in developing framework. In this paper, a Digital Forensic Framework that can detect intrusion within heterogeneous joint clouds was developed with the architectural model and algorithm that can handle the joint clouds heterogeneity and complexity during inter-clouds resources management. This study originates a new framework and an algorithm that enable detecting crime and locating a scene of a crime for digital investigation (digital forensic) in a joined different configured cloud service providers (CSPs) platforms. Contribution/Originality: This study originates a new framework and an algorithm that enable detecting crime and locating a scene of a crime for digital investigation (digital forensic) in a joined different Configured cloud service providers (CSPs) platforms. 1. INTRODUCTION Cloud computing technology renders the acquisition of hardware and software by the industrial institutions and academic institutions useless, as sensitive data and/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), Microsoft Azure and others, provide services to cloud-end users on a pay-as-you-go service, the users only pay cloud resources utilized [1]. Today, various Cloud Service Providers (CSPs) are aiming to interoperable clouds. The effort is to aggregate or join different forms of cloud service providers, to one cloud platform [2]. Some scholars also have indicated broad interest in creating a cloud-of-clouds where multiple cloud service providers can gain access to resources of each other seamlessly; this can be referred to as a multi-cloud [3]. The main issues with joining multiple and differently configured cloud service providers are enormous, most of the cloud systems are not compatible with one another and cannot share services with one another since everyone speaks a different language [4]. There are no specified service standards that are specific to the effort of joining two or more clouds and these standards are deployed on
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...
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