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Controller area network (CAN) is used as a legacy protocol for in-vehicle communication. However, it lacks basic security features such as message authentication, integrity, confidentiality, etc., because the sender information in the message is missing. Hence, it is prone to different attacks like spoofing attacks, denial of service attacks, man in the middle and masquerade attacks. Researchers have proposed various techniques to detect and prevent these attacks, which can be split into two classes: (a) MAC-based techniques and (b) intrusion detection-based techniques. Further, intrusion detection systems can be divided into four categories: (i) message parameter- based, (ii) entropy-based, (iii) machine Learning-based and (iv) fingerprinting-based. This paper details state-of- the-art survey of fingerprinting-based intrusion detection techniques. In addition, the advantages and limitations of different fingerprinting-based intrusion detection techniques methods will be discussed.

This paper will provide an Overview of Automotive Cyber Security Standards related to the Vehicle OBD-II Data Link. The OBD-II Connector Attack Tree is described with respect to the SAE J3138 requirements for Intrusive vs. non-Intrusive Services. A proposed test method for SAE J3138 is described including hardware and software scripting. Finally, example test results are reviewed and compared with a potential threat boundary.

A ranked list of value exchanges is created based on the impact of cybersecurity on the stakeholder map. System level-losses are identified from high impact value exchanges, which can then be fed into the step 1 of STPA-Sec analysis.

As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.

The paper includes a description of cybersecurity measures to protect the vehicle against malicious attacks.

In recent years, with increase in external connectivity (V2X, telematics, mobile projection, BYOD) the automobile is becoming a target of cyberattacks and intrusions. Any such intrusion reduces customer trust in connected cars and negatively impacts brand image (like the recent Jeep Cherokee hack). To protect against intrusion, several mechanisms are available. These range from a simple secure CAN to a specialized symbiote defense software. A few systems (e.g. V2X) implement detection of an intrusion (defined as a misbehaving entity). However, most of the mechanisms require a system-wide change which adds to the cost and negatively impacts the performance. In this paper, we are proposing a practical and scalable approach to intrusion detection. Some benefits of our approach include use of existing security mechanisms such as TrustZone® and watermarking with little or no impact on cost and performance. In addition, our approach is scalable and does not require any system-wide changes.

In addition, due to the cyber-security risk, the security functions to ensure the integrity of the message has to be considered.

This paper deals with an integrated motor-transmission (IMT) speed tracking control of the connected vehicle when there are controller area network (CAN)-induced delays and denial of service (DOS)-induced delays. A connected vehicle equipped with an IMT system may be attacked through the external network. Therefore, there are two delays on the CAN of the connected vehicle, which are CAN-induced and cyber-attack delays. A DOS attack generates huge delays in CAN and even makes the control system invalid. To address this problem, a robust dynamic output-feedback controller of the IMT speed tracking system considering event-triggered detectors resisting CAN-induced delays and DOS-induced delays is designed. The event-triggered detector is used to reduce the CAN-induced network congestion with appropriate event trigger conditions on the controller input and output channels. CAN-induced delays and DOS-induced delays are modeled by polytopic inclusions using the Taylor series expansion.

In the past, aircraft network design did not demand for information security considerations. The aircraft systems were simple, obscure, proprietary and, most importantly for security, the systems have been either physically isolated or they have been connected by directed communication links. The union of the aircraft systems thus formed a federated network. These properties are in sharp contrast with today’s system designs, which rest upon platform-based solutions with shared resources being interconnected by a massively meshed and shared communication network. The resulting connectivity and the high number of interfaces require an in-depth security analysis as the systems also provide functions that are required for the safe operation of the aircraft. This network design evolution, however, resulted in an iterative and continuous adaption of existing network solutions as these have not been developed from scratch.

Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.

Due to the rapid development in the technological aspect of the autonomous vehicle (AV), there is a compelling need for research in the field vehicle efficiency and emission reduction without affecting the performance, safety and reliability of the vehicle. Electric vehicle (EV) with rechargeable battery has been proved to be a practical solution for the above problem. In order to utilize the maximum capacity of the battery, a proper power management and control mechanism need to be developed such that it does not affect the performance, reliability and safety of vehicle. Different optimization techniques along with deterministic dynamic programming (DDP) approach are used for the power distribution and management control. The battery-operated electric vehicle can be recharged either by plug-in a wired connection or by the inductive mean (i.e. wirelessly) with the help of the electromagnetic field energy.

Unmanned ground vehicles (UGVs) may encounter difficulties accommodating environmental uncertainties and system degradations during harsh conditions. However, human experience and onboard intelligence can may help mitigate such cases. Unfortunately, human operators have cognition limits when directly supervising multiple UGVs. Ideally, an automated decision aid can be designed that empowers the human operator to supervise the UGVs. In this paper, we consider a connected UGV platoon under cyber attacks that may disrupt safety and degrade performance. An observer-based resilient control strategy is designed to mitigate the effects of vehicle-to-vehicle (V2V) cyber attacks. In addition, each UGV generates both internal and external evaluations based on the platoons performance metrics. A cloud-based trust-based information management system collects these evaluations to detect abnormal UGV platoon behaviors.

The caveat to these additional capabilities is issues like cybersecurity, complexity, etc. This paper is an exploration into FuSa and CAVs and will present a systematic approach to understand challenges and propose potential framework, Intelligent Vehicle Monitoring for Safety and Security (IVMSS) to handle faults/malfunctions in CAVs, and specifically autonomous systems.

In the past, research on blockchain technology has addressed security and privacy concerns within intelligent transportation systems for critical V2I and V2V communications that form the backbone of Internet of Vehicles. Within trucking industry, a recent trend has been observed towards the use of blockchain technology for operations. Industry stakeholders are particularly looking forward to refining status quo contract management and vehicle maintenance processes through blockchains. However, the use of blockchain technology for enhancing vehicle performance in fleets, especially while considering the fact that modern-day intelligent vehicles are prone to cyber security threats, is an area that has attracted less attention. In this paper, we demonstrate a case study that makes use of blockchains to securely optimize the fuel economy of fleets that do package pickup and delivery (P&D) in urban areas.

In-vehicle networks used for inter-ECU communication, most commonly the CAN bus, were not designed with cybersecurity in mind, and as a result, communication by corrupt devices connected to the bus is not authenticated.

The SAE AS2C Standard AS5506C Architecture Analysis and Description Language (AADL) is a modeling language for predictive analysis of real-time software reliant, safety and cybersecurity critical systems that provides both the precision of formal modeling and the tool-agnostic freedom of a text-based representation. ...AADL supports multiple domains of architectural analysis such as timing, latency, resources, safety, scheduling, and cybersecurity. Adventium Labs conducted an exercise to determine the applicability of software engineering practices (e.g., continuous integration (CI), application programming interface (API) sharing, test driven development (TDD)) to the AADL-based Architecture Centric Virtual Integration Process (ACVIP).

The results of this work is allowed to identify a number of cybersecurity threats of the automated security-critical automotive systems, which reduces the efficiency of operation, road safety and system safety. ...According to the evaluating criterion of board electronics, the presence of poorly-protected communication channels, the 75% of the researched modern vehicles do not meet the minimum requirements of cybersecurity due to the danger of external blocking of vital systems. The revealed vulnerabilities of the security-critical automotive systems lead to the necessity of developing methods for mechanical and electronic protection of the modern vehicle. ...The law of normal distribution of the mid-points of the expert evaluation of the cyber-security of a modern vehicle has been determined. Based on the system approach, ranking of the main cybersecurity treats is performed.

Traditional Cybersecurity solutions fall short in meeting automotive ECU constraints such as zero false positives, intermittent connectivity, and low performance impact. ...We integrated Autonomous Security on a BeagleBone Black (BBB) system to evaluate the feasibility of mitigating Cybersecurity risks against potential threats. We identified key metrics that should be measured, such as level of security, ease of integration and system performance impact.

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.

The ever-increasing complexity and connectivity of driver assist functions pose challenges for both Functional Safety and Cyber Security. Several of these challenges arise not only due to the new functionalities themselves but due to numerous interdependencies between safety and security. Safety and security goals can conflict, safety mechanisms might be intentionally triggered by attackers to impact functionality negatively, or mechanisms can compete for limited resources like processing power or memory to name just some conflict potentials. But there is also the potential for synergies, both in the implementation as well as during the development. For example, both disciplines require mechanisms to check data integrity, are concerned with freedom from interference and require architecture based analyses. So far there is no consensus in the industry on how to best deal with these interdependencies in automotive development projects.