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Mamun, A. Al, Mamun, M. Abdullah Al, Shikfa, A..  2018.  Challenges and Mitigation of Cyber Threat in Automated Vehicle: An Integrated Approach. 2018 International Conference of Electrical and Electronic Technologies for Automotive. :1–6.
The technological development of automated vehicles opens novel cybersecurity threats and risks for road safety. Increased connectivity often results in increased risks of a cyber-security attacks, which is one of the biggest challenges for the automotive industry that undergoes a profound transformation. State of the art studies evaluated potential attacks and recommended possible measures, from technical and organizational perspective to face these challenges. In this position paper, we review these techniques and methods and show that some of the different solutions complement each other while others overlap or are even incompatible or contradictory. Based on this gap analysis, we advocate for the need of a comprehensive framework that integrates technical and organizational mitigation measures to enhance the cybersecurity of automotive vehicles.
Kim, M., Jang, I., Choo, S., Koo, J., Pack, S..  2017.  Collaborative security attack detection in software-defined vehicular networks. 2017 19th Asia-Pacific Network Operations and Management Symposium (APNOMS). :19–24.

Vehicular ad hoc networks (VANETs) are taking more attention from both the academia and the automotive industry due to a rapid development of wireless communication technologies. And with this development, vehicles called connected cars are increasingly being equipped with more sensors, processors, storages, and communication devices as they start to provide both infotainment and safety services through V2X communication. Such increase of vehicles is also related to the rise of security attacks and potential security threats. In a vehicular environment, security is one of the most important issues and it must be addressed before VANETs can be widely deployed. Conventional VANETs have some unique characteristics such as high mobility, dynamic topology, and a short connection time. Since an attacker can launch any unexpected attacks, it is difficult to predict these attacks in advance. To handle this problem, we propose collaborative security attack detection mechanism in a software-defined vehicular networks that uses multi-class support vector machine (SVM) to detect various types of attacks dynamically. We compare our security mechanism to existing distributed approach and present simulation results. The results demonstrate that the proposed security mechanism can effectively identify the types of attacks and achieve a good performance regarding high precision, recall, and accuracy.

Xinhai Zhang, Persson, M., Nyberg, M., Mokhtari, B., Einarson, A., Linder, H., Westman, J., DeJiu Chen, Torngren, M..  2014.  Experience on applying software architecture recovery to automotive embedded systems. Software Maintenance, Reengineering and Reverse Engineering (CSMR-WCRE), 2014 Software Evolution Week - IEEE Conference on. :379-382.

The importance and potential advantages with a comprehensive product architecture description are well described in the literature. However, developing such a description takes additional resources, and it is difficult to maintain consistency with evolving implementations. This paper presents an approach and industrial experience which is based on architecture recovery from source code at truck manufacturer Scania CV AB. The extracted representation of the architecture is presented in several views and verified on CAN signal level. Lessons learned are discussed.