CAN node reliability assessment using segmented discrete time Markov chains

<span lang="EN-US">Real-time communication is important in control network. In real-time communication, message need to be delivered from source to destination within specification. Embedded Ethernet and Controller Area Network (CAN) protocol can be used in control network to achieve hard real-time communication. For embedded Ethernet protocol, Carrier Sense Multiple Access with Collision Detection (CSMA/CD) is the media access control (MAC) used to control data transmission between nodes in network. Back-off algorithm in CSMA/CD is used to handle packet collisions and retransmission. For CAN protocol, it is communication protocol developed mainly for automotive application. It has priority arbitration to handle collisions and retransmission. In this project, embedded Ethernet network models and CAN network models are developed and simulated in MATLAB Simulink software. Several back-off algorithms, which are Binary Exponential Backoff (BEB), Linear Back-off Algorithm, Exponential-Linear back-off Algorithm and Logarithm Back-off Algorithm are proposed and implemented into Embedded Ethernet network model to evaluate the performance. Both embedded Ethernet and CAN network models are extended to 3 nodes, 10 nodes, and 15 nodes to evaluate performance at different network condition. The performance criteria evaluated and discussed are average delay and jitter of packets. The results show that in network with high number of nodes, Linear Back-off Algorithm and Exponential-Linear back-off Algorithm shows improvement in packets delay and jitter. For CAN network, the packet jitter is relatively low.</span>

Controller Area Network (CAN) is the main bus network that connects electronic control units in automobiles. Although CAN protocols have been revised to improve the vehicle safety, the security weaknesses of CAN have not been fully addressed. Security threats on automobiles might be from external wireless communication or from internal malicious CAN nodes mounted on the CAN bus. Despite of various threat sources, the security weakness of CAN is the root of security problems. Due to the limited computation power and storage capacity on each CAN node, there is a lack of hardware-efficient protection methods for the CAN system without losing the compatibility to CAN protocols. To save the cost and maintain the compatibility, we propose to exploit the built-in CAN fault confinement mechanism to detect the masquerade attacks originated from the malicious CAN devices on the CAN bus. Simulation results show that our method achieves the attack misdetection rate at the order of 10-5 and reduces the encryption latency by up to 68% over the complete frame encryption method.

<div class="section abstract"><div class="htmlview paragraph">The amount of data communicated in automotive networks is increasing rapidly, leading to more complex systems alongside the rising number of Electronic Control Units (ECUs) in modern vehicles. As the number of ECUs has risen, Controller Area Network (CAN) communication bandwidth has been pushed to its limit. Existing solutions - such as using multiple CAN buses, sending multiple CAN frames or switching to another protocol - require a significant system-design effort and replacement of hardware and software. This has paved the way for CAN Flexible Data-rate (CAN FD), which extends the CAN standard and permits significantly higher data rates, enabling faster firmware upgrades. However, some changes must be made like: exchange the classical CAN microcontroller with a CAN FD microcontroller and also a CAN FD transceiver must be used.</div><div class="htmlview paragraph">This article will explore the benefits of CAN FD, how it compares with the classical CAN protocol, requirements for systems and how to introduce CAN FD into existing CAN networks.</div></div>

The Controller Area Network (CAN) is widely used for distributed systems in automotive and other applications such as safety-critical applications. As such, it is necessary to evaluate the property of the continuous working ability of a CAN node. In this paper we setup a discrete time Malkov chain model based on the fault confinement mechanisms of CAN to calculate how long a CAN node can work normally before it goes into its "bus-off" state. An example will be given to show the theoretical conclusion finally.

Virtual instrumentation has experienced significant advancements in recent decades, providing efficient and reliable solutions for the connection and communication of electronic devices in various applications. This article explores the most relevant developments in the field, focusing on the integration of Controller Area Network (CAN) networks and microcontrollers in distributed sensor projects. The article also presents a case study in which a CAN network is implemented along with the ESPWroom32 microcontroller in a distributed sensor project for alcoholic beverage production. The sensors used in each stage of the process, such as ultrasonic, load, water level, and motion sensors, are described, highlighting the importance of redundancy in monitoring critical parameters to ensure safety and proper process operation.

Controller area network (CAN) data-reduction techniques have been developed to reduce CAN bus loads, which have increased due to the large number of electronic control units in modern automobiles. Automotive communication uses various in-vehicle network. These techniques make it possible that same information to be sent using less bandwidth. However, the existing CAN DR algorithms only consider the CAN network. Automotive communication uses various in-vehicle network (IVN) protocols such as CAN, FlexRay, and Ethernet. The use of DR techniques may cause compatibility issue in heterogenous IVNs. This paper proposes a gateway system for data-reduced communication between Ethernet and CAN systems with data-reduction. The proposed gateway system receives a compressed CAN message, decompresses it, and transmits it to the Ethernet network. Additionally, the gateway receives a normal Ethernet message, compresses it, and transmits it to the CAN protocol. An evaluation of the performance of the developed gateway system is also presented.

Controller Area Network (CAN) protocol is a well-established and widely accepted communication technology for in-vehicle communications. However, the increase in the number of sensors deployed in cars brings complexity and cost to the automobile industry since CAN is a wired network. So, short range wireless communications technologies that operate in unlicensed band are seen as potential alternative to CAN network. Bluetooth is considered as a highly promising candidate for such intra-vehicle wireless networks. This paper uses a CAN to Bluetooth gateway which enables the conversion of CAN message into Bluetooth message. This is necessary to achieve the wireless communication via Bluetooth modules. On the other hand, it is necessary to maintain the reliability of communication that is offered by wired network, CAN. This paper aims to investigate experimentally, the level of reliability that is offered by wireless networks using these gateways. A lab car is used for experimental purpose which introduces closed environment and the Non-Line-of-Site (NLoS) paths between the Bluetooth modules. Finally, this paper proposes a suitable model for in-vehicle wireless networks.

This paper presents induction motor control system operation using matrix converter based on the controller area network (CAN). The hardware control system is designed with dual microcontrollers which communicate to each other by a dual-port RAM. The advantages of matrix converter are utilized with the CAN network on the field oriented control method of induction motor. The performances of the motor control fully guarantee the system stability and the successful data communication by network. The experimental results are given on 5Hp induction motor to verify the effectiveness and feasibility of the control system using network.

The concept of Controller Area Network (CAN) has been largely used in real-time automatically control applications such as the systems used in industries, automobiles, aircraft, and automated factories. If installing CAN network is in dispersed authentic time applications mortally requires increasing the scope of spread the area, and communicate freely with other Local Area Networks and self-governing novel CAN segments or remote CAN 2.0 nodes. This has efficient highly secured distributed real time control serial communication protocol. Its application areas are from high speed networks to low cost multiplex wiring. In automotive electronics, engine control units, sensors, control unit systems, etc. are connected using CAN with bitrates up to 1 Mbps. At the same time it is cost effective to build into vehicle body electronics, e.g. lamp clusters, electric windows etc. to replace the wiring harness otherwise required. A purpose to implement an interworking device called Wireless Interworking Unit (WIU) which is enabling local/remote CAN2.0A nodes to commune over IEEE 802.11b WLAN (MAC) using packet encapsulation method. By using this method a smart network can be implemented for intelligent, self governed, automated, energy hoarder work in vehicles, machines, robots, space aircrafts etc. Computer simulation modeling of such idea is very beneficial for any small industries, organization. This paper presents simulation modeling results for WIU using NS-2 TOOL.

The response time distributions of the frames sent on a Controller Area Network (CAN) bus are of prime interest to dimension and validate automotive electronic architectures. However, the existing work on the timing behaviour of the CAN network does not take into account that all the data exchanges between the Electronic Control Units (ECUs) are driven by different and independent clocks which are subject to clock drifts. This paper proposes a model for clock drifts and describes their impact on the CAN frame response time distributions. By implementing the clock drifts in a CAN simulation tool, we show experimentally that the response time distributions converge, for drift values chosen randomly within the same range on all ECUs, whatever the initial phasings between the sending nodes. Furthermore, we show that, as a result of the clock drifts, the situations leading to the worst case response times are transient.

The increasing cyber-physical integration in connected and autonomous vehicles (CAVs) has amplified the need for robust intrusion detection systems (IDS) to secure controller area network (CAN) communications. Existing deep learning approaches, such as CNNs and LSTMs, have demonstrated strong potential but often struggle to detect stealthy and sophisticated attacks, primarily due to inadequate temporal modeling and the use of datasets with limited fidelity that do not reflect real-world attack complexities. To address these limitations, we propose an optimized hybrid IDS model that integrates one-dimensional convolutional neural networks (1D-CNN) with bidirectional long short-term memory (BiLSTM) layers. The architecture is specifically designed to extract spatio-temporal features from CAN traffic with minimal complexity, enabling efficient detection of subtle attack patterns. Our model incorporates a time-aware design that allows it to detect attacks as they evolve, even when they occur in localized segments of the payload. It was trained and evaluated using the high-fidelity ORNL ROAD dataset, which includes physically validated fuzzing and targeted CAN ID attacks. The proposed model achieved an accuracy of 99.73%, a Matthews Correlation Coefficient (MCC) of 0.9401, and maintained average low false positive of (≤ 0.00045) and false negative of (≤ 0.00047) rates. It also demonstrated a low average prediction latency of 0.535 milliseconds per CAN frame, highlighting its architectural efficiency. This performance reflects a deliberate design balance between lightweight complexity and high detection accuracy, advancing the development of practical and robust deep learning-based IDS solutions for modern vehicular networks.

Time-synchronization technology can provide a common notion of time among the participating nodes on a network. This is essential not only for protocol operation for time-critical services but also for the time stamp for information included in the message. Precise time information can be very crucial for such things as autonomous driving because there are various sensor measurements from multiple cameras, and radio detection and ranging (radar) and light detection and ranging (LiDAR) are used for perceiving the current situation via sensor fusion. A well-known synchronization method, IEEE 1588, denoted as the precision time protocol (PTP), can be used for various applications. For in-vehicle networks of autonomous cars, we have to consider that the network may be comprised of subnetworks based on different protocols such as controller area network (CAN) and Ethernet. However, implementing PTPs on such heterogeneous vehicle networks causes several problems. First, the PTP procedure must be modified to be implement on a CAN network. Second, to calculate the delay and offset for PTP, the processing delay that occurs during message conversion must be considered. In this paper, we propose a synchronization method for CAN–Ethernet networks to solve these problems. The performance of the proposed synchronization method is evaluated by experiments on a real CAN–Ethernet network.

A new error handling algorithm for controller area network in networked control system

As modern vehicles continue to evolve, advanced technologies are integrated to enhance the driving experience. A key enabler of this advancement is the Controller Area Network (CAN) bus, which facilitates seamless communication between vehicle components. Despite its widespread adoption, the CAN bus was not designed with security as a priority, making it vulnerable to various attacks. In this paper, we propose CANGuard, an Intrusion Detection System (IDS) designed to detect attacks on the CAN network and identify the originating node in real time. Using a simulated CAN-enabled system with four nodes representing diverse vehicle components, we generated a dataset featuring Denial-of-Service (DoS) attacks by exploiting the arbitration feature of the CAN bus, which prioritizes high-criticality messages (e.g., engine control) over lower-criticality ones (e.g., infotainment). We trained and evaluated several machine learning models for their ability to detect attacks and pinpoint the responsible node. Results indicate that Gradient Boosting outperformed other models, achieving high accuracy in both attack detection and node identification. While the Multi-Layer Perceptron (MLP) model demonstrated strong attack detection performance, it struggled with node identification, achieving less than 50% accuracy. These findings underscore the potential of tree-based models for real-time IDS applications in CAN-enabled vehicles.

Modern vehicles are governed by a network of Electronic Control Units (ECUs), which are programmed to sense inputs from the driver and the environment, to process these inputs, and to control actuators that, e.g., regulate the engine or even control the steering system. ECUs within a vehicle communicate via automotive bus systems such as the Controller Area Network (CAN), and beyond the vehicles boundaries through upcoming vehicle-to-vehicle and vehicle-to-infrastructure channels. Approaches to manipulate the communication between ECUs for the purpose of security testing and reverse-engineering of vehicular functions have been presented in the past, all of which struggle with automating the detection of system change in response to message injection. In this paper we present our findings with fuzzing CAN networks, in particular while observing individual ECUs with a sensor harness. The harness detects physical responses, which we then use in a oracle functions to inform the fuzzing process. We systematically define fuzzers, fuzzing configurations and oracle functions for testing ECUs. We evaluate our approach based on case studies of commercial instrument clusters and with an experimental framework for CAN authentication. Our results show that the approach is capable of identifying interesting ECU states with a high level of automation. Our approach is applicable in distributed cyber-physical systems beyond automotive computing.