UROP Project
AI/ML Based Vulnerability Detection in Windows Binaries
Cybersecurity, AI, Computing
Research Mentor: Dr. Sharanya Jayaraman, She/her
Department, College, Affiliation: Computer Science, Arts and Sciences
Contact Email: sjayaraman@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Computer Science, Arts and Sciences
Contact Email: sjayaraman@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Computer Science, Computer Engineering, or IT preferred, but anyone interested in Cybersecurity is welcome
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 6-8, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 2
Relevant Majors: Computer Science, Computer Engineering, or IT preferred, but anyone interested in Cybersecurity is welcome
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 6-8, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Friday, September 5
Start Time: 12:30
End Time: 1:00
Zoom Link: https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Ffsu.zoom.us%2Frec%2Fshare%2FN1LPumVpDW15LEg6cxHPJFaqN1qxVrgQkm4Ya0BD0O2uCNcmnCFvLjJRQNWz7J5Y.68_F-kZiXQdyiivj&data=05%7C02%7Csj11n%40fsu.edu%7C4d0619e881224e3cbe0608ddec9ecb64%7Ca36450ebdb0
Project Description
In this project, we explore how Artificial Intelligence (AI) can help us find security problems in Windows programs—without needing to take them apart. We use tools like Convolutional Neural Networks (CNNs), which are good at recognizing patterns, and Markov Chains, which help us understand how things change over time.Instead of disassembling the program (which can be complicated and risky), we treat the program like a "black box" and analyze its behavior and structure from the outside. This makes the process faster and safer, and it opens up new ways to detect malware or bugs that could be exploited.
For students, this project offers a hands-on introduction to AI, cybersecurity, and software analysis. You’ll learn how to work with real-world data, train models, and think critically about how computers can learn to spot problems. The techniques we develop could help improve antivirus software, make systems more secure, and even influence how future software is built and tested.
Research Tasks: Students may be expected to perform one or more of these tasks based on experience and interest:
1. Literature Review & Background Research
- Explore fundamental concepts in AI, CNNs, Markov Chains, and binary analysis.
- Summarize existing approaches to malware detection and static analysis.
2. Data Collection & Preprocessing
- Gather sample Windows binaries (safe and legal ones).
- Learn how to extract features from binaries without disassembly (e.g., byte-level patterns, entropy measures).
3. Evaluate model performance using metrics like accuracy, precision, and recall.
4. Tool Development
- Build scripts to automate analysis tasks (e.g., scanning binaries, logging results).
- Create simple user interfaces or dashboards to visualize findings.
5. Security Implications & Ethical Considerations
- Discuss how this approach could improve malware detection.
- Reflect on ethical concerns in AI and cybersecurity (e.g., false positives, privacy).
6. Documentation & Presentation
- Maintain clear documentation of methods and results.
- Prepare posters or presentations for research showcases or conferences.
Skills that research assistant(s) may need: Required:
- Critical Thinking: Interpreting results, debugging models, and ethical reasoning
- Communication: Writing reports, presenting findings, collaborating in teams
Recommended:
- Math Foundations: Basic probability, linear algebra, and statistics
- Python
Mentoring Philosophy
As a mentor, I view undergraduate research as a transformative experience—one that introduces students not only to the rigor of academic inquiry but also to the joy and complexity of discovery. My mentoring philosophy centers on fostering independence while providing a reliable scaffold of support. I encourage students to explore the research process with curiosity and initiative, knowing that I am there to guide them through moments of uncertainty, frustration, and breakthrough.Recognizing that many undergraduate students enter research with limited experience, I strive to create an environment that balances the thrill of working at the frontier of knowledge with the discipline of evidence-based reasoning and empirical analysis. I believe that early exposure to the iterative nature of research—its trials, errors, and unexpected turns—helps students build resilience and develop a deeper appreciation for the scientific method.
Above all, I aim to instill in my students the understanding that research is not merely a means to an end, but a journey to be savored. In a world increasingly driven by instant results, I emphasize the value of patience, perseverance, and reflection. Successful researchers are not defined solely by their findings, but by their commitment to the process of inquiry and their ability to learn from each step along the way.
Through this philosophy, I hope to cultivate not just capable researchers but thoughtful, self-aware individuals who carry the spirit of inquiry into their future academic and professional pursuits.