On the Feasibility of Hybrid Homomorphic Encryption for Intelligent Transportation Systems

TL;DR

This paper explores hybrid homomorphic encryption (HHE) as a practical solution for privacy-preserving data processing in Intelligent Transportation Systems, significantly reducing communication overhead while maintaining security.

Contribution

It develops theoretical models and evaluates the HHE scheme Rubato, demonstrating substantial reductions in ciphertext size for ITS applications.

Findings

HHE reduces ciphertext size by orders of magnitude compared to traditional HE.

HHE maintains cryptographic security while improving efficiency.

Evaluation shows HHE is suitable for latency-sensitive ITS environments.

Abstract

Many Intelligent Transportation Systems (ITS) applications require strong privacy guarantees for both users and their data. Homomorphic encryption (HE) enables computation directly on encrypted messages and thus offers a compelling approach to privacy-preserving data processing in ITS. However, practical HE schemes incur substantial ciphertext expansion and communication overhead, which limits their suitability for time-critical transportation systems. Hybrid homomorphic encryption (HHE) addresses this challenge by combining a homomorphic encryption scheme with a symmetric cipher, enabling efficient encrypted computation while dramatically reducing communication cost. In this paper, we develop theoretical models of representative ITS applications that integrate HHE to protect sensitive vehicular data. We then perform a parameter-based evaluation of the HHE scheme Rubato to estimate ciphertext sizes and communication overhead under realistic ITS workloads. Our results show that HHE achieves orders-of-magnitude reductions in ciphertext size compared with conventional HE while maintaining cryptographic security, making it significantly more practical for latency-constrained ITS communication.