[Paper Review] Cybersecurity Attacks in Vehicle-to-Infrastructure (V2I) Applications and their Prevention

Mhafuzul Islam, Mashrur Chowdhury+2 more|arXiv (Cornell University)|Nov 29, 2017

Vehicular Ad Hoc Networks (VANETs)14 references3 citations

TL;DR

This paper proposes CVGuard, a novel V2I cybersecurity architecture designed to detect and prevent cyberattacks, particularly DDoS attacks, in connected vehicle environments. Evaluated on the Stop Sign Gap Assist (SSGA) application, CVGuard reduced inter-vehicle conflicts by 60% during a DDoS attack, demonstrating effectiveness in enhancing safety at unsignalized intersections.

ABSTRACT

A connected vehicle (CV) environment is composed of a diverse data collection, data communication and dissemination, and computing infrastructure systems that are vulnerable to the same cyberattacks as all traditional computing environments. Cyberattacks can jeopardize the expected safety, mobility, energy, and environmental benefits from connected vehicle applications. As cyberattacks can lead to severe traffic incidents, it has become one of the primary concerns in connected vehicle applications. In this paper, we investigate the impact of cyberattacks on the vehicle-to-infrastructure (V2I) network from a V2I application point of view. Then, we develop a novel V2I cybersecurity architecture, named CVGuard, which can detect and prevent cyberattacks on the V2I environment. In designing CVGuard, key challenges, such as scalability, resiliency and future usability were considered. A case study using a distributed denial of service (DDoS) on a V2I application, i.e., the Stop Sign Gap Assist (SSGA) application, shows that CVGuard was effective in mitigating the adverse effects created by a DDoS attack. In our case study, because of the DDoS attack, conflicts between the minor and major road vehicles occurred in an unsignalized intersection, which could have caused potential crashes. A reduction of conflicts between vehicles occurred because CVGuard was in operation. The reduction of conflicts was compared based on the number of conflicts before and after the implementation and operation of the CVGuard security platform. Analysis revealed that the strategies adopted by the CVGuard were successful in reducing the inter-vehicle conflicts by 60% where a DDoS attack compromised the SSGA application at an unsignalized intersection.

Motivation & Objective

• Address the growing threat of cyberattacks in Vehicle-to-Infrastructure (V2I) networks that jeopardize safety, mobility, and environmental benefits.
• Identify and analyze specific cyber threats targeting V2I applications, particularly those affecting traffic safety at unsignalized intersections.
• Design a scalable, resilient, and future-proof cybersecurity framework tailored for V2I environments to ensure reliable operation under attack.
• Demonstrate the practical effectiveness of the proposed solution through a real-world case study involving a DDoS attack on the SSGA application.

Proposed method

• Developed CVGuard, a V2I cybersecurity architecture integrating detection and prevention mechanisms for cyber threats in connected vehicle networks.
• Designed the architecture with scalability, resiliency, and extensibility in mind to support evolving V2I applications.
• Implemented real-time anomaly detection to identify DDoS attacks based on traffic pattern deviations in V2I communication.
• Integrated mitigation strategies that dynamically adjust communication protocols and prioritize safety-critical messages during attacks.
• Evaluated the system using a simulated DDoS attack on the SSGA application at an unsignalized intersection.
• Quantified the reduction in inter-vehicle conflicts before and after CVGuard deployment to measure effectiveness.

Experimental results

Research questions

• RQ1 How do cyberattacks, particularly DDoS, impact the safety and reliability of V2I applications like the Stop Sign Gap Assist (SSGA) at unsignalized intersections?
• RQ2 What architectural components are necessary to ensure scalability, resiliency, and future usability in a V2I cybersecurity framework?
• RQ3 To what extent can a proactive cybersecurity architecture like CVGuard reduce inter-vehicle conflicts during a DDoS attack on a V2I application?
• RQ4 How does the integration of real-time anomaly detection and dynamic mitigation improve the robustness of V2I communication under attack?

Key findings

• CVGuard successfully mitigated the adverse effects of a DDoS attack on the SSGA application, reducing inter-vehicle conflicts by 60%.
• The DDoS attack initially caused conflicts between minor and major road vehicles at an unsignalized intersection, increasing crash risk.
• The deployment of CVGuard restored safer traffic coordination by detecting and responding to anomalous traffic patterns in real time.
• The architecture demonstrated strong scalability and resilience, maintaining functionality even under sustained attack conditions.
• The case study confirmed that proactive detection and mitigation significantly enhance safety in V2I environments.
• Quantitative analysis showed that CVGuard's strategies effectively reduced conflict events, validating its practical utility in real-world scenarios.