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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.

Cyber security is becoming increasingly critical in the car industry. Not only the entry points to the external world in the car need to be protected against potential attack, but also the on-board communication in the car require to be protected against attackers who may try to send unauthorized CAN messages. However, the current CAN network was not designed with security in mind. As a result, the extra measures have to be taken to address the key security properties of the secure CAN communication, including data integrity, authenticity, confidentiality and freshness. While integrity and authenticity can be achieved by using a relatively straightforward algorithms such as CMAC (Cipher-based Message Authentication Code) and Confidentiality can be handled by a symmetric encryption algorithm like AES128 (128-bit Advanced Encryption Standard), it has been recognized to be more challenging to achieve the freshness of CAN message.

CAN bus network proved to be efficient and dynamic for small compact cars as well as heavy-duty vehicles (HDV). However, HDVs are more susceptible to malicious attacks due to lack of security in their intra-vehicle communication protocols. SAE proposed a new standard named J1939-91C for CAN-FD networks which provides methods for establishing trust and securing mutual messages with optional encryption. J1939-91C ensures message authenticity, integrity, and confidentiality by implementing complex cryptographic operations including hash functions and random key generation. In this paper, the three main phases of J1939-91C, i.e., Network Formation, Rekeying, and Message Exchange, are simulated and tested on Electronic Control Units (ECUs) supporting CAN-FD network. Numerous test vectors were generated and validated to support SAE J1939-91C. The mentioned vectors were produced by simulating different encryption and hashing algorithms with variable message and key lengths.

With the development of vehicle intelligence and the Internet of Vehicles, how to protect the safety of the vehicle network system has become a focus issue that needs to be solved urgently. The Controller Area Network (CAN) bus is currently a very widely used vehicle-mounted bus, and its security largely determines the degree of vehicle-mounted information security. The CAN bus lacks adequate protection mechanisms and is vulnerable to external attacks such as replay attacks, modifying attacks, and so on. On the basis of the existing work, this paper proposes an authentication method that combines Hash-based Message Authentication Code (HMAC)-SHA256 and Tiny Encryption Algorithm (TEA) algorithms. This method is based on dynamic identity authentication in challenge/response made and combined with the characteristics of the CAN bus itself as it achieves the identity authentication between the gateway and multiple electronic control units (ECUs).

Upon their arrival, Unmanned Autonomous Systems (UAS) brought with them many benefits for those involved in a military campaign. They can use such systems to reconnoiter dangerous areas, provide 24-hr aerial security surveillance for force protection purposes or even attack enemy targets all the while avoiding friendly human losses in the process. Unfortunately, these platforms also carry the inherent risk of being built on innately vulnerable cybernetic systems. From software which can be tampered with to either steal data, damage or even outright steal the aircraft, to the data networks used for communications which can be jammed or even eavesdropped on to gain access to sensible information. All this has the potential to turn the benefits of UAS into liabilities and although the last decade has seen great advances in the development of protection and countermeasures against the described threats and beyond the risk still endures.

Automotive system functionalities spread over a wide range of sub-domains ranging from non-driving related components to complex autonomous driving related components. The requirements to design and develop these components span across software, hardware, firmware, etc. elements. The successful development of these components to achieve the needs from the stockholders requires accurate understanding and traceability of the requirements of these component systems. The high-level customer requirements transformation into low level granularity requires an efficient requirement engineer. The manual understanding of the customer requirements from the requirement documents are influenced by the context and the knowledge gap of the requirement engineer in understanding and transforming the requirements.