Collecting and Classifying Security and Privacy Design Patterns for Connected Vehicles

Collecting and Classifying Security and Privacy Design Patterns for Connected Vehicles: SECREDAS Approach

Marko, N.
Vasenev, A.
Striecks, C.

2020

In the past several years, autonomous driving turned out tobe a target for many technical players. Automated driving requires newand advanced mechanisms to provide safe functionality and the increased communication makes automated vehicles more vulnerable to attacks. Security is already well-established in some domains, such as the IT sector, and now spills over to Automotive. In order to not reinvent the wheel, existing security methods and tools can be evaluated and adaptedto be applicable in other domains, such as Automotive. In the EuropeanH2020 ECSEL project SECREDAS, this approach is followed and existing methods, tools, protocols, best practices etc. are analyzed, combinedand improved to be applicable in the field of connected vehicles. To provide modular and reusable designs, solutions are collected in form of design patterns. The SECREDAS design patterns describe solution templates to solve security, safety and privacy issues related to automated systems. The grouping and classification of design patterns is important to facilitate the selection process which is a challenging task and weak classification schemes can be a reason for a sparse application of security patterns, which represent a subgroup of design patterns. This work aims to assist automotive software and systems engineers in adopting andusing technologies available on the market. The SECREDAS security patterns are based on existing technologies, so-called Common Technology Elements, and describe how and where to apply them in contextof connected vehicles by making a reference to a generic architecture.This allows developers to easily find solutions to common problems andreduces the development effort by providing concrete, trustworthy solu-tions. The whole approach and classification scheme is illustrated basedon one example security pattern.

Artificial intelligence
Automation
Computer software reusability
Embedded systems
Safety engineering
System of systems
Vehicles
Automated driving
Automated vehicles
Automotive software
Autonomous driving

http://resolver.tudelft.nl/uuid:72f46416-4079-4e1e-9efd-15ddbb2960ca

https://doi.org/10.1007/978-3-030-55583-2_3

884287

Springer Science and Business Media Deutschland GmbH

9783030555825

0302-9743

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15th Workshop on Dependable Smart Embedded and Cyber-Physical Systems and Systems-of-Systems, DECSoS 2020, 1st International Workshop on Dependable Development-Operation Continuum Methods for Dependable Cyber-Physical Systems, DepDevOps 2020, 1st International Workshop on Underpinnings for Safe Distributed AI, USDAI 2020, and 3rd International Workshop on Artificial Intelligence Safety Engineering, WAISE 2020, held in conjunction with the 39th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2020, 15 September 2020 through 18 September 2020, 36-53

conference paper