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Description
The increasing usage of smart-phones and mobile devices in work environment and IT

industry has brought about unique set of challenges and opportunities. ARM architecture

in particular has evolved to a point where it supports implementations across wide spectrum

of performance points and ARM based tablets and smart-phones are in demand. The

enhancements to

The increasing usage of smart-phones and mobile devices in work environment and IT

industry has brought about unique set of challenges and opportunities. ARM architecture

in particular has evolved to a point where it supports implementations across wide spectrum

of performance points and ARM based tablets and smart-phones are in demand. The

enhancements to basic ARM RISC architecture allow ARM to have high performance,

small code size, low power consumption and small silicon area. Users want their devices to

perform many tasks such as read email, play games, and run other online applications and

organizations no longer desire to provision and maintain individual’s IT equipment. The

term BYOD (Bring Your Own Device) has come into being from demand of such a work

setup and is one of the motivation of this research work. It brings many opportunities such

as increased productivity and reduced costs and challenges such as secured data access,

data leakage and amount of control by the organization.

To provision such a framework we need to bridge the gap from both organizations side

and individuals point of view. Mobile device users face issue of application delivery on

multiple platforms. For instance having purchased many applications from one proprietary

application store, individuals may want to move them to a different platform/device but

currently this is not possible. Organizations face security issues in providing such a solution

as there are many potential threats from allowing BYOD work-style such as unauthorized

access to data, attacks from the devices within and outside the network.

ARM based Secure Mobile SDN framework will resolve these issues and enable employees

to consolidate both personal and business calls and mobile data access on a single device.

To address application delivery issue we are introducing KVM based virtualization that

will allow host OS to run multiple guest OS. To address the security problem we introduce

SDN environment where host would be running bridged network of guest OS using Open

vSwitch . This would allow a remote controller to monitor the state of guest OS for making

important control and traffic flow decisions based on the situation.
ContributorsChowdhary, Ankur (Author) / Huang, Dijiang (Thesis advisor) / Tong, Hanghang (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Emerging trends in cyber system security breaches in critical cloud infrastructures show that attackers have abundant resources (human and computing power), expertise and support of large organizations and possible foreign governments. In order to greatly improve the protection of critical cloud infrastructures, incorporation of human behavior is needed to predict

Emerging trends in cyber system security breaches in critical cloud infrastructures show that attackers have abundant resources (human and computing power), expertise and support of large organizations and possible foreign governments. In order to greatly improve the protection of critical cloud infrastructures, incorporation of human behavior is needed to predict potential security breaches in critical cloud infrastructures. To achieve such prediction, it is envisioned to develop a probabilistic modeling approach with the capability of accurately capturing system-wide causal relationship among the observed operational behaviors in the critical cloud infrastructure and accurately capturing probabilistic human (users’) behaviors on subsystems as the subsystems are directly interacting with humans. In our conceptual approach, the system-wide causal relationship can be captured by the Bayesian network, and the probabilistic human behavior in the subsystems can be captured by the Markov Decision Processes. The interactions between the dynamically changing state graphs of Markov Decision Processes and the dynamic causal relationships in Bayesian network are key components in such probabilistic modelling applications. In this thesis, two techniques are presented for supporting the above vision to prediction of potential security breaches in critical cloud infrastructures. The first technique is for evaluation of the conformance of the Bayesian network with the multiple MDPs. The second technique is to evaluate the dynamically changing Bayesian network structure for conformance with the rules of the Bayesian network using a graph checker algorithm. A case study and its simulation are presented to show how the two techniques support the specific parts in our conceptual approach to predicting system-wide security breaches in critical cloud infrastructures.
ContributorsNagaraja, Vinjith (Author) / Yau, Stephen S. (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2015