Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems
Eniola Adamson - Tennessee State University
Co-Author(s): Eliakin del Rosario, Gabriel Ramos, and Lyssa Williams, University of Virgin Islands, Virgin Islands James Gadson, Allen University, SC
Modern day technology has increased the need for Cyber Security. For there are a multitude of attacks that are launched on a daily basis, equaling up to millions sent out every month. The definition of Cyber Security defined by Merriam Webster is stated as: measures taken to protect a computer or computer system (as on the Internet) against unauthorized access or attack. There are plenty of documented infamous attacks that have made headlines over the past five years in the United States. Cyber Security has influenced different projects and thorough research. We conducted basic research to develop a Cyber Analysis, Simulation and Experimentation Environment (CASE-V) for enhancing situational awareness and decision support capabilities for cyber defense and cyber training. The purpose of building the test-bed is to improve cyber defense awareness and help cyber security learners and practitioners improve proficiency on the job and in training. It will be a valuable resource for cyber security research education, and practice tool for universities, agencies, and the nation as a whole. In developing the test bed, the several attributes included are: Intrusion Detection System, Machine Learning, Statistical Distributions, Modeling and Simulations, and the Framework Development.
As cyber threats grow in uniqueness, network protectors are being outclassed by uniquely developed threats. Data mining techniques, such as Classifications, provide a prediction mechanism that can be used to detect these threats. To further study prediction mechanisms, an integrated platform containing substantial amount of tools and resources is essential. Using machine learning, data modeling, and algorithm simulation, we can construct models to predict possible unknown threats from patterns obtained from known data. The logic can then be incorporated into Intrusion Detection System signatures and custom-built detection scripts. This process in return enhances network protector’s abilities to defend against cyber threats. We were able to accomplish all this by conducting basic research to develop a Cyber Analysis, Simulation and Experimentation Environment (CASE-V) for enhancing situational awareness and decision support capabilities for cyber defense and cyber training.
Future research into the Case-V test bed, will be the web interface added on top of the framework. As of now it requires users to have a basic knowledge of cyber security and machine learning; since the framework was built in command line. A web user interface will allow users who do not have that knowledge to use the tool. The Case-V test bed was designed, where if users wanted to add more capabilities such as data analytics it will be possible. We also plan on researching and furthering our knowledge of MiniMega’s capability; which is a tool for launching and managing the virtual machines and is implementation of the test bed.
Funder Acknowledgement(s): This research was funded and continues to be funded by NSF HBCU-UP Award # 1533515, DOD Award #FA8750-15-2-0120 and DOE Award # DE-NA0002686
Faculty Advisor: Sachin Shetty,