2022 Design and Research Conference

Security Probability 

Team Members: Jacob DuMontier, Sydney Holland, Carrick Inabnett, Kevin Ortiz

Advisor: Dr. Pradeep Chowriappa

Security Probability is a program designed to scrape a subject’s social media page and determine the likelihood of a hacker using this information to correctly guess the answer to each of their security questions.

Dynamically Generated Covert Channel (DGCC)

Team Name: Robust Information Production Systems (RIPS)

Team Members: Raven Alexander, Jack Foil, Peter Ford, Jacob Mathews

Advisor: Dr. Miguel Gates

Have you ever wondered how hackers steal people’s information without being detected? Hackers and penetration testers use covert channels in cyber attacks to become undetected and steal information. Cyber professionals manually create covert channels because of the diverse and complex network environments. To combat this problem, we provide a program where the best covert channel is automatically created. RIPS created the Dynamically Generated Covert Channel (DGCC) that gathers information from a target environment to generate the best fit covert channel. The DGCC gives the user a command-line interface to personalize the covert channel. Therefore, it allows the typical penetration tester to create the best communication median between the host and the target.

Coordination Platform for Incident Response (CooPIR)

Team Name: CooPIR Troopers

Team Members: Jonah Fitzgerald, Andrew Merrow, Alexander Petty, Joseph Siharath, Brandon Vessel

Advisor: Dr. Miguel Gates

The Coordination Platform for Incident Response is a software that combines many existing procedures and security tools into a single platform and creates a new way to collaboratively link evidence together. The platform will allow for quick response and coordination when investigating and reacting to an incident.

Active Shooter Detection System

Team Name: Team Captivating

Team Members: Megan Cox, Lauren Gilbert, Katie Hay, Matt Johnson, Austin Scioneaux

Sponsor: VSMerlot

Advisor: Dr. Miguel Gates

Active shooter situations are becoming more prevalent across America. Although preventing such events would be ideal, giving law enforcement officers the most updated and accurate information about the situation is the goal of the Active Shooter Detection System. The Active Shooter Detection System uses deep learning, for both auditory and visual detection, of a shooter and gunshots to pinpoint a shooter’s location and track them. This occurs while also sending updates about the shooter’s location to designated first responders.

R.A.P.T.O.R.(Ranking Advanced Persistent Threat Ontological Report)

Team Name: InGen-ious

Team Members: Jaimin Bhagat, James Henry, Thomas Mason, Tristan Sharpe, Welsey Venters

Advisor: Dr. Miguel Gates

In this age of ubiquitous connectivity, with virtually every device we own or operate, we are likely to become the victim of some type of cyber breach and never know the identity of the attacker. While databases of attackers and the methods used by them exist, they require a significant amount of navigating to narrow down the list of potential attackers. The aim of the R.A.P.T.O.R. is to harness these databases, initially Mitre’s Att&ck, to programmatically narrow the list of potential attackers. Based upon input of techniques, sub techniques, and software, through the graphical user interface, an HTML-based report will be generated with a list of matched attackers, the percentage match of the attacker to the user input, and mitigation recommendations, each with hyperlinks to the source information.