Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

Defending Vehicles Against Cyberthreats: Challenges and a Detection-Based Solution

The lack of concern with security when vehicular network protocols were designed some thirty years ago is about to take its toll as vehicles become more connected and smart. Today as demands for more functionality and connectivity on vehicles continue to grow, a plethora of Electronic Control Units (ECUs) that are able to communicate to external networks are added to the automobile networks. The proliferation of ECU and the increasing autonomy level give drivers more control over their vehicles and make driving easier, but at the same time they expand the attack surface, bringing more vulnerabilities to vehicles that might be exploited by hackers. Possible outcomes of a compromised vehicle range from personal information theft to human life loss, raising the importance of automotive cybersecurity to a whole different level. Therefore, network safety has become a necessary and vital consideration of a vehicle. This project is two-fold: the first half will focus on the background of vehicle cybersecurity, characteristics of vehicular networks that could be leveraged during a hacking process, including ECU, Controller Area Network (CAN bus) and On-Board Diagnostics (OBD). It also discusses and evaluates previous hacking experiments conducted by researchers and their proposed countermeasures. The second half is an evaluation of approaches to design an Intrusion Detection System (IDS). The aim of this project is to find an effective and suitable solution todefend vehicles against various types of cyber threats

Project BeARCAT : Baselining, Automation and Response for CAV Testbed Cyber Security : Connected Vehicle & Infrastructure Security Assessment

Connected, software-based systems are a driver in advancing the technology of transportation systems. Advanced automated and autonomous vehicles, together with electrification, will help reduce congestion, accidents and emissions. Meanwhile, vehicle manufacturers see advanced technology as enhancing their products in a competitive market. However, as many decades of using home and enterprise computer systems have shown, connectivity allows a system to become a target for criminal intentions. Cyber-based threats to any system are a problem; in transportation, there is the added safety implication of dealing with moving vehicles and the passengers within

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version

Proof of Travel for Trust-Based Data Validation in V2I Communication Part I: Methodology

Previous work on misbehavior detection and trust management for Vehicle-to-Everything (V2X) communication can identify falsified and malicious messages, enabling witness vehicles to report observations about high-criticality traffic events. However, there may not exist enough "benign" vehicles with V2X connectivity or vehicle owners who are willing to opt-in in the early stages of connected-vehicle deployment. In this paper, we propose a security protocol for the communication between vehicles and infrastructure, titled Proof-of-Travel (POT), to answer the research question: How can we transform the power of cryptography techniques embedded within the protocol into social and economic mechanisms to simultaneously incentivize Vehicle-to-Infrastructure (V2I) data sharing activities and validate the data? The key idea is to determine the reputation of and the contribution made by a vehicle based on its distance traveled and the information it shared through V2I channels. In particular, the total vehicle miles traveled for a vehicle must be testified by digital signatures signed by each infrastructure component along the path of its movement. While building a chain of proofs of spatial movement creates burdens for malicious vehicles, acquiring proofs does not result in extra cost for normal vehicles, which naturally want to move from the origin to the destination. The proof of travel for a vehicle can then be used to determine the contribution and reward by its altruistic behaviors. We propose short-term and long-term incentive designs based on the POT protocol and evaluate their security and performance through theoretical analysis and simulations