Robust and secure resource management for automotive cyber-physical systems

2022 Spring.Includes bibliographical references.Modern vehicles are examples of complex cyber-physical systems with tens to hundreds of interconnected Electronic Control Units (ECUs) that manage various vehicular subsystems. With the shift towards autonomous driving, emerging vehicles are being characterized by an increase in the number of hardware ECUs, greater complexity of applications (software), and more sophisticated in-vehicle networks. These advances have resulted in numerous challenges that impact the reliability, security, and real-time performance of these emerging automotive systems. Some of the challenges include coping with computation and communication uncertainties (e.g., jitter), developing robust control software, detecting cyber-attacks, ensuring data integrity, and enabling confidentiality during communication. However, solutions to overcome these challenges incur additional overhead, which can catastrophically delay the execution of real-time automotive tasks and message transfers. Hence, there is a need for a holistic approach to a system-level solution for resource management in automotive cyber-physical systems that enables robust and secure automotive system design while satisfying a diverse set of system-wide constraints. ECUs in vehicles today run a variety of automotive applications ranging from simple vehicle window control to highly complex Advanced Driver Assistance System (ADAS) applications. The aggressive attempts of automakers to make vehicles fully autonomous have increased the complexity and data rate requirements of applications and further led to the adoption of advanced artificial intelligence (AI) based techniques for improved perception and control. Additionally, modern vehicles are becoming increasingly connected with various external systems to realize more robust vehicle autonomy. These paradigm shifts have resulted in significant overheads in resource constrained ECUs and increased the complexity of the overall automotive system (including heterogeneous ECUs, network architectures, communication protocols, and applications), which has severe performance and safety implications on modern vehicles. The increased complexity of automotive systems introduces several computation and communication uncertainties in automotive subsystems that can cause delays in applications and messages, resulting in missed real-time deadlines. Missing deadlines for safety-critical automotive applications can be catastrophic, and this problem will be further aggravated in the case of future autonomous vehicles. Additionally, due to the harsh operating conditions (such as high temperatures, vibrations, and electromagnetic interference (EMI)) of automotive embedded systems, there is a significant risk to the integrity of the data that is exchanged between ECUs which can lead to faulty vehicle control. These challenges demand a more reliable design of automotive systems that is resilient to uncertainties and supports data integrity goals. Additionally, the increased connectivity of modern vehicles has made them highly vulnerable to various kinds of sophisticated security attacks. Hence, it is also vital to ensure the security of automotive systems, and it will become crucial as connected and autonomous vehicles become more ubiquitous. However, imposing security mechanisms on the resource constrained automotive systems can result in additional computation and communication overhead, potentially leading to further missed deadlines. Therefore, it is crucial to design techniques that incur very minimal overhead (lightweight) when trying to achieve the above-mentioned goals and ensure the real-time performance of the system. We address these issues by designing a holistic resource management framework called ROSETTA that enables robust and secure automotive cyber-physical system design while satisfying a diverse set of constraints related to reliability, security, real-time performance, and energy consumption. To achieve reliability goals, we have developed several techniques for reliability-aware scheduling and multi-level monitoring of signal integrity. To achieve security objectives, we have proposed a lightweight security framework that provides confidentiality and authenticity while meeting both security and real-time constraints. We have also introduced multiple deep learning based intrusion detection systems (IDS) to monitor and detect cyber-attacks in the in-vehicle network. Lastly, we have introduced novel techniques for jitter management and security management and deployed lightweight IDSs on resource constrained automotive ECUs while ensuring the real-time performance of the automotive systems

In-vehicle communication networks : a literature survey

The increasing use of electronic systems in automobiles instead of mechanical and hydraulic parts brings about advantages by decreasing their weight and cost and providing more safety and comfort. There are many electronic systems in modern automobiles like antilock braking system (ABS) and electronic brakeforce distribution (EBD), electronic stability program (ESP) and adaptive cruise control (ACC). Such systems assist the driver by providing better control, more comfort and safety. In addition, future x-by-wire applications aim to replace existing braking, steering and driving systems. The developments in automotive electronics reveal the need for dependable, efficient, high-speed and low cost in-vehicle communication. This report presents the summary of a literature survey on in-vehicle communication networks. Different in-vehicle system domains and their requirements are described and main invehicle communication networks that have been used in automobiles or are likely to be used in the near future are discussed and compared with key references

Extensible FlexRay communication controller for FPGA-based automotive systems

Modern vehicles incorporate an increasing number of distributed compute nodes, resulting in the need for faster and more reliable in-vehicle networks. Time-triggered protocols such as FlexRay have been gaining ground as the standard for high-speed reliable communications in the automotive industry, marking a shift away from the event-triggered medium access used in controller area networks (CANs). These new standards enable the higher levels of determinism and reliability demanded from next-generation safety-critical applications. Advanced applications can benefit from tight coupling of the embedded computing units with the communication interface, thereby providing functionality beyond the FlexRay standard. Such an approach is highly suited to implementation on reconfigurable architectures. This paper describes a field-programmable gate array (FPGA)-based communication controller (CC) that features configurable extensions to provide functionality that is unavailable with standard implementations or off-the-shelf devices. It is implemented and verified on a Xilinx Spartan 6 FPGA, integrated with both a logic-based hardware ECU and a fully fledged processor-based electronic control unit (ECU). Results show that the platform-centric implementation generates a highly efficient core in terms of power, performance, and resource utilization. We demonstrate that the flexible extensions help enable advanced applications that integrate features such as fault tolerance, timeliness, and security, with practical case studies. This tight integration between the controller, computational functions, and flexible extensions on the controller enables enhancements that open the door for exciting applications in future vehicles

VEGa : a high performance vehicular Ethernet gateway on hybrid FPGA

Modern vehicles employ a large amount of distributed computation and require the underlying communication scheme to provide high bandwidth and low latency. Existing communication protocols like Controller Area Network (CAN) and FlexRay do not provide the required bandwidth, paving the way for adoption of Ethernet as the next generation network backbone for in-vehicle systems. Ethernet would co-exist with safety-critical communication on legacy networks, providing a scalable platform for evolving vehicular systems. This requires a high-performance network gateway that can simultaneously handle high bandwidth, low latency, and isolation; features that are not achievable with traditional processor based gateway implementations. We present VEGa, a configurable vehicular Ethernet gateway architecture utilising a hybrid FPGA to closely couple software control on a processor with dedicated switching circuit on the reconfigurable fabric. The fabric implements isolated interface ports and an accelerated routing mechanism, which can be controlled and monitored from software. Further, reconfigurability enables the switching behaviour to be altered at run-time under software control, while the configurable architecture allows easy adaptation to different vehicular architectures using high-level parameter settings. We demonstrate the architecture on the Xilinx Zynq platform and evaluate the bandwidth, latency, and isolation using extensive tests in hardware

A NOVEL APPROACH FOR FLEXRAY PROTOCOL WITH CONFIDENTIALITY AND AUTHENTICITY

Master'sMASTER OF ENGINEERIN

A robust, reliable and deployable framework for In-vehicle security

Cyber attacks on financial and government institutions, critical infrastructure, voting systems, businesses, modern vehicles, etc., are on the rise. Fully connected autonomous vehicles are more vulnerable than ever to hacking and data theft. This is due to the fact that the protocols used for in-vehicle communication i.e. controller area network (CAN), FlexRay, local interconnect network (LIN), etc., lack basic security features such as message authentication, which makes it vulnerable to a wide range of attacks including spoofing attacks. This research presents methods to protect the vehicle against spoofing attacks. The proposed methods exploit uniqueness in the electronic control unit electronic control unit (ECU) and the physical channel between transmitting and destination nodes for linking the received packet to the source. Impurities in the digital device, physical channel, imperfections in design, material, and length of the channel contribute to the uniqueness of artifacts. I propose novel techniques for electronic control unit (ECU) identification in this research to address security vulnerabilities of the in-vehicle communication. The reliable ECU identification has the potential to prevent spoofing attacks launched over the CAN due to the inconsideration of the message authentication. In this regard, my techniques models the ECU-specific random distortion caused by the imperfections in digital-to-analog converter digital to analog converter (DAC), and semiconductor impurities in the transmitting ECU for fingerprinting. I also model the channel-specific random distortion, impurities in the physical channel, imperfections in design, material, and length of the channel are contributing factors behind physically unclonable artifacts. The lumped element model is used to characterize channel-specific distortions. This research exploits the distortion of the device (ECU) and distortion due to the channel to identify the transmitter and hence authenticate the transmitter.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/154568/1/Azeem Hafeez Final Disseration.pdfDescription of Azeem Hafeez Final Disseration.pdf : Dissertatio