Securing Connected Vehicle Applications with an Efficient Dual Cyber-Physical Blockchain Framework

Abstract: While connected vehicle (CV) applications have the potential to revolutionize traditional transportation system, cyber and physical attacks on them could be devastating. In this work, we propose an efficient dual cyber-physical blockchain framework to build trust and secure communication for CV applications. Our approach incorporates blockchain technology and physical sensing capabilities of vehicles to quickly react to attacks in a large-scale vehicular network, with low resource overhead. We explore the application of our framework to three CV applications, i.e., highway merging, intelligent intersection management, and traffic network with route choices. Simulation results demonstrate the effectiveness of our blockchain-based framework in defending against spoofing attacks, bad mouthing attacks, and Sybil and voting attacks. We also provide analysis to demonstrate the timing efficiency of our framework and the low computation, communication, and storage overhead for its implementation.

• The paper introduces a dual blockchain framework that rapidly identifies malicious behaviors and verifies message integrity in connected vehicles.
• It employs a dual structure with a trust points blockchain for immediate responses and a proof-of-travel blockchain for long-term trust verification.
• The framework shows resilience against spoofing, bad-mouthing, and Sybil attacks while maintaining scalability with low computational overhead.

Securing Connected Vehicle Applications with an Efficient Dual Cyber-Physical Blockchain Framework

Introduction

Connected Vehicle (CV) applications promise to transform transportation systems through enhanced communication and coordination among vehicles. However, CV systems face significant security challenges due to their susceptibility to cyber and physical attacks. This paper addresses these challenges by proposing a dual cyber-physical blockchain framework to secure communications and build trust in CV applications.

Dual Blockchain Framework Design

The proposed framework consists of two blockchain systems: the trust points blockchain and the proof-of-travel blockchain. These blockchains are designed to be efficient and scalable, suitable for large-scale vehicular networks.

Trust Points Blockchain

The trust points blockchain is dedicated to rapidly identifying and exposing malicious behaviors with low overhead. It leverages vehicles' physical sensing capabilities to verify message integrity, ensuring that falsified messages are detected promptly. Smart contracts within the blockchain facilitate instantaneous voting, redressing, and transferring records, allowing the network to quickly update trust estimates for vehicles upon detecting suspicious activity.

Proof-of-Travel Blockchain

This blockchain records vehicles' long-term contributions by tracking their interactions and communications over time. The proof-of-travel blockchain relies on historical data and provides a mechanism for establishing vehicle trust in scenarios where immediate past behavior cannot be verified. By aggregating travel history and message interactions, this component of the framework complements the fast-response capabilities of the trust points blockchain.

Security and Efficiency

The framework employs a stake-based consensus model, similar to Algorand, where a vehicle's stake is determined by its accumulated proof-of-travel credits and trust points. This prevents attacks by malicious users who attempt to manipulate the network with significant computational resources.

Defending Against Attacks

Three types of attacks are of particular interest: message spoofing, bad-mouthing, and Sybil attacks. The framework's dual blockchain design demonstrates resilience against these threats through simulations:

• Message Spoofing Attacks: When vehicles attempt to mislead others about their state, the blockchain framework can rapidly detect inconsistencies and adjust vehicle behavior accordingly, minimizing disruptions.
• Bad Mouthing Attacks: In scenarios where honest vehicles are unfairly penalized, the framework's redressing mechanism ensures that correct trust assessments are reinstated efficiently.
• Sybil Attacks: By combining short-term trust evaluations with long-term travel histories, the framework effectively counters attempts to flood the network with false identities.

Resource Demand and Scalability

The framework's design prioritizes low computational, communication, and storage overheads by employing techniques like sharding across geographic regions for distributed ledger maintenance. The overall design anticipates significant scalability, with latency and bandwidth utilization being carefully evaluated.

Round Latency and Region Size

The relationship between round latency and region size is analyzed, demonstrating that proper configuration enables responsive and scalable blockchain operations. The trade-off between real-time performance and communication overhead is a critical consideration, ensuring both security and efficiency.

Conclusion

The dual blockchain framework proposed in this paper provides an innovative approach to securing CV applications. It combines cyber and physical elements to deliver a robust, efficient, and scalable solution that addresses key vulnerabilities in connected vehicle ecosystems. Future work will focus on optimizing the framework's efficiency and implementation in real-world deployments, enabling widespread adoption of secure CV applications.