Inspiration
As someone concentrating in cybersecurity, I wanted to integrate that into my project. So I looked at problems that dealt with both cybersecurity and quantum, and landed on a topic that is prominent today: encryption.
What it does
This project treats that as an optimization problem. Each campus system is a yes/no decision, scored by money spent plus risk left behind. Risk combines three factors: what the data is worth, how vulnerable its current encryption is to quantum attack, and how much of the data’s secrecy lifetime falls after quantum computers arrive
How we built it
Qiskit, running on the Aer simulator and on IBM hardware. The model is a weighted vertex-cover variant: a connection only counts as protected when both of its endpoints are upgraded, which makes the problem quadratic and means systems can’t be ranked individually. Vendor-locked systems are eliminated before the circuit is built rather than penalized inside it, which drops 8 decisions to a 6-qubit circuit.
Challenges we ran into
Getting the model right mattered more than the circuit. My first version treated regulations as systems, which is wrong.
Accomplishments that we're proud of
I am proud of the circuit accounting for so many different variables and its real-world applicability. I could see myself using this project in a different context.
What we learned
I learned the basics of quantum computing and why it is useful. I learned how it could be applied for risk assessment and planning for different organizations.
Built With
- aersimulator
- claude
- ibmquantum
- pycharm
