Tanmay Singal

Publication Date

Spring 2025

Degree Type

Master's Project

Degree Name

Master of Science in Computer Science (MSCS)

Department

Computer Science

First Advisor

Thomas Austin

Second Advisor

Katerina Potika

Third Advisor

Robert Chun

Keywords

Faceted values, Homomorphically Encrypted Faceted Values, Scheme Homomorphic

Abstract

Faceted values prevent the implicit flow of sensitive information by controlling the visibility of program data. They achieve this by maintaining two facets for each variable: a public facet, which is observable, and a private facet, which remains hidden. Although this method secures the flow of sensitive data, it can be leaked if the server storing the faceted values is compromised. While faceted values may be encrypted on the server, doing so would necessitate that the private facets be briefly decrypted during execution to allow arithmetic operations to be performed on them, creating an attack vector for information to be sniffed by malicious actors. To address this limitation, this paper introduces Homomorphically Encrypted Faceted Values (HEFVs), which eliminate the need to decrypt private facets during execution. Homomorphic encryption enhances security by allowing operations to be performed directly on encrypted data and preventing any information from being leaked even if the execution environment is breached. HEFVs can be securely transmitted across networks and used in distributed computing environments, as no private key is required to perform computations on the private facet. This paper further presents Scheme Homomorphic, a Scheme-like programming language that natively supports HEFVs as a data type, abstracting the complexity of both faceted values and homomorphic encryption from the user. Homomorphic encryption increases computational cost, and benchmarks show a performance overhead of up to 7x for HEFVs compared to RSA-512 encryption and an 82x overhead compared to cleartext faceted values, illustrating both the security and performance trade-offs of HEFVs in secure computing environments.

Download

Share

COinS