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Presentation
Network Analysis for Malware Intrusion Detection
ICFNJ Undergraduate Research Symposium (2018)
  • Davis Cook
  • Wilbert Chagula
  • Bianca Reilly
  • Abbey Sterner
  • Joshua Talamayan
  • Catherine Way
  • Manfred Minimair
Abstract
This study was conducted in order to determine patterns in network connections so that one may discern irregularities and therefore any potential dangers to a computer network. Clusters of network users were created for they tend to behave similarly on a network, which allowed for easier analysis of a complex system. Each cluster was assigned a probability of interacting with the others, and this data was then input into Python consoles using the package NetworkX so that team members could analyze and form conclusions collaboratively. Simulation results would consist of nodes and edges representing user clusters and connections, respectively. By adjusting time intervals in which we observe interactions, patterns and the normal behavior of clusters could then be determined. With these patterns in mind, abnormalities and irregular behavior could be identified more easily.
The possible impact of the outcomes of this experiment include the ability to determine when there is an unknown user in a network. This can be useful for companies or organizations trying to determine if there is an unauthorized user or if they are being hacked. As of recently, we have managed to simulate different client and server connections and examine them to determine a pattern. An exact definition of unusual server behavior has yet be stated, but generally any frequency of connections outside of those depicted in a normal bell-shaped curve are being examined. Additionally, we are working on Python code to access more data available on the Internet.
Keywords
  • network analysis,
  • cybersecurity
Disciplines
Publication Date
Spring March 5, 2018
Location
Liberty Science Center, Jersey City, New Jersey
Citation Information
Davis Cook, Wilbert Chagula, Bianca Reilly, Abbey Sterner, et al.. "Network Analysis for Malware Intrusion Detection" ICFNJ Undergraduate Research Symposium (2018)
Available at: http://works.bepress.com/minimair/33/