Abstract:

Homomorphic encryption (HE) enables computation on encrypted data, ensuring that sensitive information remains confidential throughout processing. This study explores the feasibility of applying two widely used HE schemes for secure grade computation in Bachelor’s and Master’s study programs. We developed a prototype web application that performs grade calculations on an external server while preserving full data privacy. Users locally encrypt their grade data, after which all arithmetic operations are executed directly on the encrypted values; only the final grade is decrypted on the client side.

Our performance evaluation compares computation times across encryption schemes, parameter settings, and individual calculation steps. The results demonstrate that HE-based grade processing is feasible for web-based client–server applications, achieving practical runtimes (<1 s) and offering expert users transparent control over cryptographic parameters.

This work contributes:
(1) a real-world demonstration of privacy-preserving academic grade computation using HE, and
(2) an educational use case that allows students to interactively experience HE through their own sensitive data.

We further discuss implementation challenges, performance trade-offs, and potential extensions of HE in educational systems, aiming to guide future research on privacy-preserving technologies in the academic domain.

Keywords:

Grade Calculation, Homomorphic Encryption.