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Automotive researchers and industry experts have extensively documented vulnerabilities arising from unauthorized in-vehicle communication through academic research, industry investigations, sponsored events, and learnings from real-world attacks. While current cybersecurity endeavors in the heavy-duty (HD) vehicle space focus on securing conventional communication technologies such as the controller area network (CAN), there is a notable deficiency in defensive research concerning legacy technologies, particularly those utilized between trucks and trailers. In fact, state-of-the-art attacks on these systems have only come to public attention through official disclosures and public presentations as recently as 2020. To address these risks, this paper introduces a system-wide security concept called Legacy Intrusion Detection System (LIDS) for heavy-duty vehicle applications utilizing the SAE J1708/J1587 protocol stack.

Autonomous truck and trailer configurations face challenges when operating in reverse due to the lack of sensing on the trailer. It is anticipated that sensor packages will be installed on existing trailers to extend autonomous operations while operating in reverse in uncontrolled environments, like a customer's loading dock. Power Line Communication (PLC) between the trailer and the tractor cannot support high bandwidth and low latency communication. This paper explores the impact of using Ethernet or a wireless medium for commercial trailer-tractor communication on the lifecycle and operation of trailer electronic control units (ECUs) from a Systems Engineering perspective to address system requirements, integration, and security. Additionally, content-based and host-based networking approaches for in-vehicle communication, such as Named Data Networking (NDN) and IP-based networking are compared.

The lack of inherent security controls makes traditional Controller Area Network (CAN) buses vulnerable to Machine-In-The-Middle (MitM) cybersecurity attacks. Conventional vehicular MitM attacks involve tampering with the hardware to directly manipulate CAN bus traffic. We show, however, that MitM attacks can be realized without direct tampering of any CAN hardware. Our demonstration leverages how diagnostic applications based on RP1210 are vulnerable to Machine-In-The-Middle attacks. Test results show SAE J1939 communications, including single frame and multi-framed broadcast and on-request messages, are susceptible to data manipulation attacks where a shim DLL is used as a Machine-In-The-Middle. The demonstration shows these attacks can manipulate data that may mislead vehicle operators into taking the wrong actions.

Practical encryption is an important tool in improving the cybersecurity posture of vehicle data loggers and engineering tools. However, low-cost embedded systems struggle with reliably capturing and encrypting all frames on the vehicle networks. In this paper, implementations of symmetric and asymmetric algorithms were used to perform envelope encryption of session keys with symmetric encryption algorithms while logging vehicle controller area network (CAN) traffic. Maintaining determinism and minimizing latency are primary considerations when implementing cryptographic solutions in an embedded system. To satisfy the timing requirements for vehicle systems, the memory-mapped Cryptographic Acceleration Unit (mmCAU) on the NXP K66 processor enabled 6.4Mb/sec symmetric encryption rates, which enables logging of multiple channels at 100% bus load. Using AES-128 in Cipher Block Chaining (CBC) mode provides the encryption for data confidentiality.

Crashes involving Cummins powered heavy vehicles can damage the electronic control module (ECM) containing heavy vehicle event data recorder (HVEDR) records. When ECMs are broken and data cannot be extracted using vehicle diagnostics tools, more invasive and low-level techniques are needed to forensically preserve and decode HVEDR data. A technique for extracting non-volatile memory contents using non-destructive board level techniques through the available in-circuit debugging port is presented. Additional chip level data extraction techniques can also provide access to the HVEDR data. Once the data is obtained and preserved in a forensically sound manner, the binary record is decoded to reveal typical HVDER data like engine speed, vehicle speed, accelerator pedal position, and other status data. The memory contents from the ECM can be written to a surrogate and decoded with traditional maintenance and diagnostic software.

Cyber assurance of heavy trucks is a major concern with new designs as well as with supporting legacy systems. Many cyber security experts and analysts are used to working with traditional information technology (IT) networks and are familiar with a set of technologies that may not be directly useful in the commercial vehicle sector. To help connect security researchers to heavy trucks, a remotely accessible testbed has been prototyped for experimentation with security methodologies and techniques to evaluate and improve on existing technologies, as well as developing domain-specific technologies. The testbed relies on embedded Linux-based node controllers that can simulate the sensor inputs to various heavy vehicle electronic control units (ECUs). The node controller also monitors and affects the flow of network information between the ECUs and the vehicle communications backbone.

The proper investigation of crashes involving commercial vehicles is critical for fairly assessing liability and damages, if they exist. In addition to traditional physics based approaches, the digital records stored within heavy vehicle electronic control modules (ECMs) are useful in determining the events leading to a crash. Traditional methods of extracting digital data use proprietary diagnostic and maintenance software and require a functioning ECM. However, some crashes induce damage that renders the ECM inoperable, even though it may still contain data. As such, the objective of this research is to examine the digital record in an ECM and understand its meaning. The research was performed on a Detroit Diesel DDEC V engine control module. The data extracted from the flash memory chips include: Last Stop Record, two Hard Brake events, and the Daily Engine Usage Log. The procedure of extracting and reading the memory chips is explained.

Concepts of forensic soundness as they are currently understood in the field of digital forensics are related to the digital data on heavy vehicle electronic control modules (ECMs). An assessment for forensic soundness addresses: 1) the integrity of the data, 2) the meaning of the data, 3) the processes for detecting or predicting errors, 4) transparency of the operation, and 5) the expertise of the practitioners. The integrity of the data can be verified using cryptographic hash functions. Interpreting and understanding the meaning of the data is based on standards or manufacturer software. Comparison of interpreted ECM data to external reference measurements is reviewed from the current literature. Meaning is also extracted from interpreting hexadecimal data based on the J1939 and J1587 standards. Error detection and mitigation strategies are discussed in the form of sensor simulators to eliminate artificial fault codes.