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Automotive electronics and enterprise IT are converging and thus open the doors for advanced hacking. With their immediate safety impact, cyberattacks on such systems will endanger passengers. Today, there are various methods of security verification and validation in the automotive industry. However, we realize that vulnerability detection is incomplete and inefficient with classic security testing. In this article, we show how an enhanced Grey-Box Penetration Test (GBPT) needs less test cases while being more effective in terms of coverage and indicating less false positives.

A broad range of information is being delivered to and used within modern vehicles. Information-based applications are becoming more highly integrated into the automobile. Security services are necessary to provide appropriate protection for this information. Encryption, digital signature, and hash functionalities enable information security services such as confidentiality, authentication, integrity and non-repudiation. However, the consumer of in-vehicle information services will not accept security services that introduce any inconvenience to their activities. This paper will discuss various security service methods and security management systems and propose methods to integrate these services acceptably into vehicle-based applications.

We propose a security-testing framework to analyze attack feasibilities for automotive control software by integrating model-based development with model checking techniques. Many studies have pointed out the vulnerabilities in the Controller Area Network (CAN) protocol, which is widely used in in-vehicle network systems. However, many security attacks on automobiles did not explicitly consider the transmission timing of CAN packets to realize vulnerabilities. Additionally, in terms of security testing for automobiles, most existing studies have only focused on the generation of the testing packets to realize vulnerabilities, but they did not consider the timing of invoking a security testing. Therefore, we focus on the transmit timing of CAN packets to realize vulnerabilities. In our experiments, we have demonstrated the classification of feasible attacks at the early development phase by integrating the model checking techniques into a virtualized environment.