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Black-Box Testing for Security-Informed Safety of Automated Driving Systems
Rise Research Institutes of Sweden, Borås, Sweden.
Rise Research Institutes of Sweden, Borås, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-7235-6888
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-5269-3900
2021 (English)In: IEEE Vehicular Technology Conference, Institute of Electrical and Electronics Engineers Inc. , 2021, article id 9448691Conference paper, Published paper (Refereed)
Abstract [en]

An evaluation of safety and security properties performed by an independent organisation can be an important step towards establishing trust in Automated Driving Systems (ADS), bridging the gap between the marketing portrayal and the actual performance of such systems in real operating conditions. However, due to the complexity of an ADS's behaviour and dangers involved in performing real environment security attacks, we believe assessments that can be performed with a combination of simulation and validation at test facilities is the way forward.In this paper, we outline an approach to derive test suites applicable to generic ADS feature classes, where classes would have similar capabilities and comparable assessment results. The goal is to support black box testing of such feature classes as part of an independent evaluation. By the means of co-simulation of post-attack behaviour and critical scenarios, we derive a representative set of physical certification tests, to gain an understanding of the interplay between safety and security. During the initial tests an ADS is subjected to various attacks and its reactions recorded. These reactions such as reduced functionality, fall back etc., together with relevant scenarios for the class is further analysed to check for safety implications. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2021. article id 9448691
Keywords [en]
Automated Driving Systems, Black-box testing, Dependability, Safety, Safety Assessment, Security, Deceleration, Safety testing, Certification tests, Real environments, Real operating conditions, Safety and securities, Security attacks, Simulation and validation, Various attacks
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:mdh:diva-55649DOI: 10.1109/VTC2021-Spring51267.2021.9448691ISI: 000687839600060Scopus ID: 2-s2.0-85112418651ISBN: 9781728189642 (print)OAI: oai:DiVA.org:mdh-55649DiVA, id: diva2:1588050
Conference
93rd IEEE Vehicular Technology Conference, VTC 2021-Spring, 25 April 2021 through 28 April 2021
Available from: 2021-08-26 Created: 2021-08-26 Last updated: 2022-04-29Bibliographically approved
In thesis
1. Towards an assessment of safety and security interplay in automated driving systems.
Open this publication in new window or tab >>Towards an assessment of safety and security interplay in automated driving systems.
2022 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

We are currently in the midst of significant changes in the road transport system, including the transformation to fossil-free propulsion and the shift to higher levels of automation. The next level in automation is soon upon us and is encompassed by the broader term Connected, Cooperative and Automated Mobility (CCAM) which is relevant for the entire transportation system. The introduction of CCAM has the potential to contribute significantly to crucial UN Sustainable Development Goals. For the automotive domain, the term Automated Driving Systems (ADS) is often used for highly automated vehicles. Notwithstanding the expected positive effects and the extraordinary efforts, highly automated driving systems are still not publicly available except in pilot programs.

The increased complexity in the higher automation levels can be ascribed to the shift from fail-safe operator support to fail-operational systems that assume the operator's role, utilising new sensors and algorithms for perception and the reliance on connectivity to solve the problem task. Here the solution is also the problem, i.e. complex systems. The complexity of the systems and difficulties in capturing a complete practical description of the environment where the systems are intended to operate pose difficulties in defining validation procedures for ADS technologies' safety, security, and trustworthiness.

Parallel to traditional safety issues, there is now a need to consider the quality of cybersecurity, e.g. due to external communication and environmental sensors being susceptible to remote attacks. A security problem may enable a hacker to incapacitate or fool an ADS resulting in unsafe behaviour. In addition to malicious misuse, the development of environment sensing has to consider functional insufficiencies of the employed sensor technologies. Therefore, both safety and security and their interplay must be addressed in developing the solutions.

The first step in gaining public confidence in the technologies involved is to raise user awareness. Therefore there is a need to be transparent and explicit on the evaluation targets and the associated supporting evidence of safe and secure ADS. An assessment of safety and security properties performed by an independent organisation can be an essential step towards establishing trust in ADS solutions, bridging the gap between the marketing portrayal and the actual performance of such systems in operating conditions.

This licentiate thesis contributes towards the overall goal of improving the assessment target and the associated supporting evidence of a safe and secure ADS in the automotive domain by (1) assessing requirements for safety, security and their interplay on key enabling technologies, (2) introducing an argument pattern enabling safety, security and interaction overlap to be jointly addressed, (3) proposing a method that enables assessment of security informed safety an independent agency.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2022
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 326
Keywords
Functional Safety, Cybersecurity, Automotive, Automated Drivning, Assessment
National Category
Embedded Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-58110 (URN)978-91-7485-554-8 (ISBN)
Presentation
2022-06-09, Kappa, Mälardalens universitet, Västerås, 13:15 (English)
Opponent
Supervisors
Available from: 2022-05-05 Created: 2022-04-26 Last updated: 2022-11-08Bibliographically approved

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Hansson, HansPunnekkat, Sasikumar

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