B-FERL: Blockchain based framework for securing smart vehicles. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Oham, Chuka; Michelin, Regio A.; Jurdak, Raja; Kanhere, Salil S.; Jha, Sanjay
• Is Part Of: Information processing & management. Volume 58:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Blockchain -- Vehicular network -- Integrity -- Electronic control units (ECUs) -- Challenge–response; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2020.102426
• Languages: English
• ISSNs: 0306-4573

Abstract

Abstract: The ubiquity of connecting technologies in smart vehicles and the incremental automation of its functionalities promise significant benefits, including a significant decline in congestion and road fatalities. However, increasing automation and connectedness broadens the attack surface and heightens the likelihood of a malicious entity successfully executing an attack. In this paper, we propose a Blockchain based Framework for sEcuring smaRt vehicLes (B-FERL). B-FERL uses permissioned blockchain technology to tailor information access to restricted entities in the connected vehicle ecosystem. It also uses a challenge–response data exchange between the vehicles and roadside units to monitor the internal state of the vehicle to identify cases of in-vehicle network compromise. In order to enable authentic and valid communication in the vehicular network, only vehicles with a verifiable record in the blockchain can exchange messages. Through qualitative arguments, we show that B-FERL is resilient to identified attacks. Also, quantitative evaluations in an emulated scenario show that B-FERL ensures a suitable response time and required storage size compatible with realistic scenarios. Finally, we demonstrate how B-FERL achieves various important functions relevant to the automotive ecosystem such as trust management, vehicular forensics and secure vehicular networks. Highlights: Securing in-vehicle network components enhances the security of smart vehicles and prevents the potential for successful remote exploitation. Integrity assessments of in-vehicle components enhances the credibility of data produced by smart vehicles. Proposed security framework satisfies critical automotive functions including vehicular forensics and trust management. Security framework facilitates the identification of compromised vehicles in the vehicular network.