On the Feasibility of Hybrid Homomorphic Encryption for Intelligent Transportation Systems

2026-02-02

AI Summary

This work addresses the high communication overhead and latency challenges posed by ciphertext expansion in traditional homomorphic encryption within intelligent transportation systems. It presents the first systematic evaluation of hybrid homomorphic encryption (HHE) for this domain, establishing theoretical models for representative applications and conducting parameterized performance analysis based on the Rubato framework. The proposed HHE scheme integrates homomorphic encryption with symmetric encryption, achieving several orders of magnitude reduction in ciphertext size while maintaining cryptographic security. This approach significantly enhances practicality in latency-sensitive scenarios, effectively balancing security and efficiency without compromising the functional requirements of real-world deployment.

Technology Category

• Search and Optimization: Heuristic Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Mixture of Experts (MoE)

Application Category

• Security and Privacy: Applications of cryptography
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Responsible Web: Data and user privacy-enhancing technologies for the Web

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.

Problem

• Intelligent Transportation Systems
• Homomorphic Encryption
• Ciphertext Expansion
• Communication Overhead
• Privacy-Preserving

Innovation

• Hybrid Homomorphic Encryption
• Intelligent Transportation Systems
• Ciphertext Expansion
• Privacy-Preserving Computation
• Communication Overhead