Cybersecurity: Malware

Team: 26

School: Manzano High

Area of Science: Cybersecurity Technology

Definition of Problem:
Our project is to make people more aware of a cyber attack called malware. Malware is a type of software that is created to intentionally damage, disrupt, and/or get access to a computer system when they aren’t supposed to; something your computer does, that you don’t want it to do. Unfortunately, not everyone is aware of malware and the many types of it.

Problem Solution:
Because solving malware is way too large of a job to get done before finals, our goal by the end of this year is to make people more aware of the dangers of malware. We will use our NetLogo model to help people to understand what it looks like and why it’s harmful. We hope that in the end the amount of people aware of malware will rise in comparison with the people that don’t.

Our Progress:
We have started creating a code based off of the Wolf and Sheep Code, that is found in the NetLogo library, and also created what we imagine Malware to look like. We’ve interviewed Christopher Goodrich, someone who works in the cybersecurity field, and our main source for our information. We have also used the suggestions of scientist, David, to build our NetLogo model.

Coding Plan:
We have created one NetLogo model, demonstrating what our initial idea of what malware was. We are now working on, and hopefully soon finishing, a new NetLogo model showing what a computer looks like while corrupted by malware. There will be two types of malware, Trojan Malware and Worm Malware, and each will have a different code. We want to show both of these types of cyber attacks and what they look like up against an anti-malware system. We also want to show a model showing what a corrupted computer system looks like in comparison to a clean computer system.

Expected Results:
We are expecting people to be more aware of Malware and all of it’s capabilities. Hopefully, they can also start protecting their computers and other devices. Although, there are so many types of Malware and it would be nearly impossible to stay protected from them all, but after speaking to Jessica Rooney, we do know that there are some steps you can take to staying safe; start with “ “.

Works Cited

Rhode, Matilda, et al. “Early-Stage Malware Prediction Using Recurrent Neural Networks.” Computers & Security, Elsevier Advanced Technology, 22 May 2018,

Team Members:

  Jerrel White
  Caitlin Woods

Sponsoring Teacher: NA

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