Browsing by Author "Vyas, Rushabh"

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    Cybersecurity education: RunLabs rapidly create virtualized labs based on a simple configuration file
    (2017) Justice, Connie; Vyas, Rushabh; Computer Information and Graphics Technology, School of Engineering and Technology
    The cornerstone in educating the future workforce in cybersecurity in higher education is experiential learning. Cybersecurity competitions are shown to have the potential to increase the workforce and encourage students to pursue the field of cybersecurity. Virtual laboratories allow emulating real life cyber threats and rapid generation of multiple scenarios and infrastructures. The purpose of RunLabs project was to create a lab infrastructure to allow instructors to generate virtualized environments rapidly. Instructors can create virtual lab for students easily, with a simple configuration file. The methods used for RunLabs creation consist of a javascript object notation (JSON) configuration file that creates virtual machines with specified network configuration. In addition, it creates virtual network computing (VNC) service for each virtual machine with a random password, which allows students to be able to access the virtual machines and work on their exercises. RunLabs has a web-based user interface for administration and an application programming interface (API). The API allows additional tools to be written around RunLabs. The administrator can reboot virtual machines, change VNC passwords. If defined in the configuration file, the administrator can create generic routing encapsulation (GRE) tunnel for the virtual machines across multiple hosts. RunLabs project used Python, Flask, SQLite, Minimega, KVM/QEMU, and OpenVSwitch as its backbone software. The analysis showed that the virtual machine host can capture virtual machines network traffic; and by default, any changes made to the virtual machines are not saved to the virtual disk. Due to the way KVM/QEMU work, one virtual disk can be used to spin up multiple virtual machines. Use case scenarios for this project included malware analysis, virtualized penetration testing network, and capture the flag competitions. Future development includes creating a virtual machine repository, bug fixes, and an option to save changes to the virtual disk. © American Society for Engineering Education, 2017.
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    Investigation of Malicious Portable Executable File Detection on the Network using Supervised Learning Techniques
    (IEEE, 2017-05) Vyas, Rushabh; Luo, Xiao; McFarland, Nichole; Justice, Connie; Computer Information and Graphics Technology, School of Engineering and Technology
    Malware continues to be a critical concern for everyone from home users to enterprises. Today, most devices are connected through networks to the Internet. Therefore, malicious code can easily and rapidly spread. The objective of this paper is to examine how malicious portable executable (PE) files can be detected on the network by utilizing machine learning algorithms. The efficiency and effectiveness of the network detection rely on the number of features and the learning algorithms. In this work, we examined 28 features extracted from metadata, packing, imported DLLs and functions of four different types of PE files for malware detection. The returned results showed that the proposed system can achieve 98.7% detection rates, 1.8% false positive rate, and with an average scanning speed of 0.5 seconds per file in our testing environment.
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    JagWaRz Junior: Cyber Security Education for Young Adolescents
    (Office of the Vice Chancellor for Research, 2015-04-17) Herbert, Jasmine; Vyas, Rushabh; Justice, Connie; Smith, Vicky
    Currently there are few methodologies for introducing cyber security to young adolescents. This area of research will examine the importance of teaching cyber security at an early age as well as the significance of introducing cyber security through the use of digital game based learning. Within this study, cyber security will be taught to a sample of young adolescents through the use of a capture the flag style game, JagWaRz Junior. The effectiveness of JagWaRz Junior will be quantitatively measured through a pretest and posttest presented to the participants. Overall, this game will encompass ways to handle many of the risks that come with Internet usage at an early age. These risks include but are not limited to cyber bullying, pornography, online predators, personal privacy, and password protection. The results of this study will contribute to our understanding of the effectiveness of digital game based pedagogic learning.