Using Epidemiology to Model Computer Viruses

Team: 27

School: Las Cruces High

Area of Science: Cybersecurity


Interim: Group Number: 27
School Name: Las Cruces High School
Area of Science: Cybersecurity
Project Title: Using Epidemiology to Model Computer Viruses

Definition of Problem:

The problem is the spread of dangerous computer viruses that can leak the personal info of thousands of individuals. These viruses infect thousands of computers a year and costs related to these attacks are set to exceed 6 trillion per year by 2021 ("60 Must-Know Cybersecurity Statistics for 2018"). The US alone has 30% of the worlds infected devices(site: Malware infects 30 percent of computers in U.S.). With the program we plan to make we plan to be able to show more about how viruses spread. This should allow those who see this model to have a better understanding of how dangerously vulnerable their networks are and why.

Method of Solving:

Our method of solving this problem is to use an infectious disease model to represent the movement of viruses through computers. We will be using Netlogo for this model because the agent interactions and networking capabilities of Netlogo is perfect for our project. In our model we will use the links available to represent the connections between the devices ("NetLogo Nw Extension"). We will also use different colors to differentiate the “infected” computers. Then we will set an arbitrary device to infected and spread the malware accordingly. We will then look at the data produced on how fast the malware spreads and which device(s) spread it quickest and therefore should be monitored. We will also make the program customizable to different networks by allowing input of how many of each device are on the network.

Progress at This Point:

At this point in time we have completed our research into networks, their vulnerabilities, and how we plan to model the threats to these networks. We began our research by determining how we will design our model. We found inspiration in a paper by R. David Parker, PhD and Csilla Farkas, PhD where they proposed an epidemiological model for modeling cyber attacks; so, since we already have an epidemiological model to use as a basis, team member Breanna Widner had coded this last year, we will focus on modifying that existing model to fit the security risks of a home network. To model this we also had to do research on home networks where we looked at how those networks are configured. We found that most home networks use peer-to-peer based technology ("What Is a Peer-To-Peer Computer Network?"). With this information we will be able to construct a basic model. Later on we will need to find more data on previous attacks to evaluate the accuracy of our model.

Expected Results:

We expect to be able to model the spread of computer viruses using data from previous historical attacks and create a model using netlogo that will accurately show how vulnerable a computer is to a certain virus. Another expectation we expect to achieve is to modify an existing Netlogo program which models epidemiology, to our specifications so we can create said model. By doing this, we will have an understanding of how easily a computer could be infected with a certain virus.

Citations:

60 Must-Know Cybersecurity Statistics for 2018. (2018, May 18). Retrieved December 5, 2018, from https://www.varonis.com/blog/cybersecurity-statistics/
Mitchell, B., & MIT. (n.d.). What Is a Peer-To-Peer Computer Network? Retrieved from https://www.lifewire.com/introduction-to-peer-to-peer-networks-817421
NetLogo Nw Extension. (n.d.). Retrieved from https://ccl.northwestern.edu/netlogo/docs/nw.html
Parker, R., PhD, & Farkas, C., PhD. (2011). Modeling Estimated Risk for Cyber Attacks: Merging Public Health and Cyber Security. Retrieved from https://cse.sc.edu/~farkas/publications/j18.pdf
Samson, T., & InfoWorld. (2012, August 08). Malware infects 30 percent of computers in U.S. Retrieved December 6, 2018, from https://www.infoworld.com/article/2618043/cyber-crime/malware-infects-30-percent-of-computers-in-u-s-.html

Team Members: Karson Million, Ben Widner, Breanna Widner, Steven Fraga

Sponsoring Teacher: Lauren Curry


Team Members:

  Karson Million
  Benjamin Widner
  Steven Fraga
  Breanna Widner

Sponsoring Teacher: Lauren Curry

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