In-vehicle Communication Network Research Articles

Dynamic Event-Triggered-Based Adaptive Finite-Time Neural Control for Active Suspension Systems With Displacement Constraint.

In this article, we give an event-based control algorithm for nonlinear active suspension systems (ASSs) with the vertical displacement constraint. For in-vehicle communication networks, the controller area network (CAN) is a widely used standard for interconnecting electronic control units (ECUs). The main task in this work is, thus, to reduce the communication burden on the CAN. To this end, we develop a dynamic event-triggered communication mechanism in ASSs. Meanwhile, in practice, the vehicle safety is degraded when the body vibration exceeds the allowable maximum. Thus, the vertical displacement of ASSs should be constrained within a reliable range. For this purpose, we present a novel finite-time integral barrier Lyapunov function (FTIBLF), which not only guarantees that the vertical displacement constraint bounds are not violated, but also enables the position of the suspension to be stabilized in the neighborhood of a desired position in finite settling time. Furthermore, neural networks (NNs) are utilized to identify the unknown nonlinear characteristics in ASSs subjected to the modeling error and unknown mass. As a result, we propose an adaptive neural control technique based on the dynamic event-triggered condition, which helps to improve the ride comfort while ensuring the driving safety and handling stability. Finally, simulation results are provided to verify the validity of the presented methodology.

Unsupervised intrusion detection system for in-vehicle communication networks

In-vehicle communication has been optimized day to day to keep updated of the technologies. Control area network (CAN) is used as a standard communication method because of its efficient and reliable connection. However, CAN is prone to several network level attacks because of its lack in security mechanisms. Various methods have been introduced to incorporate this in CAN. We proposed an unsupervised method of intrusion detection for in-vehicle communication networks by combining the optimal feature extracting ability of autoencoders and more precise clustering using fuzzy C-means (FCM). The proposed method is light weight and requires less computation time. We performed an extensive experiment and achieved an accuracy of 75.51 % with the ML350 in-vehicle intrusion dataset. By experimental result, the proposed method also works better for other intrusion detection problems like wireless intrusion detection datasets such as WNS-DS with accuracy of 84.05 % and network intrusion detection datasets such as KDDCup with accuracy 60.63 % , UNSW_NB15 with accuracy 73.62 % and Information Security Center of Excellence (ISCX) with accuracy 74.83 %. Overall, the proposed method outperforms the existing methods and avoids labeled datasets when training an in-vehicle intrusion detection model. The results of the experiment of our proposed method performed on various intrusion detection datasets indicate that the proposed approach is generalized and robust in detecting intrusions and can be effectively deployed in real time to monitor CAN traffic in vehicles and proactively alert during attacks.

Average delay analysis of soft deadline messages scheduled in the dynamic segment of FlexRay protocol

The FlexRay communication protocol provides high bandwidth for supporting both hard deadline and soft deadline traffic in in-vehicle communication networks. In this paper, we carry out delay analysis of soft deadline traffic which is handled by the dynamic segment of FlexRay. We model the arrival of these messages as Poisson processes, and use queuing theory to evaluate the average delay that they experience. Initially, we consider three nodes competing for service, assuming that two out of three can transmit messages in any FlexRay cycle and obtain expressions for the evolution of the corresponding queues. We also determine the range of message arrival rates for which the queues are stable. These results are then extended to the general case of N queues. The analytical results are compared with those obtained by simulation for a typical system.

IEEE 802.1 Zaman Hassas Araç-İçi Haberleşme Ağları için Siber Güvenlik: Güncel Gelişmeler ve Hizmet Reddi Saldırılarının Etki Analizi

Dedicated computers control the operation of Cyber Physical Systems such as in-vehicle architectures with the help of sensors and actuators. Securing the real-time communication technologies for in-vehicle platforms attracts the attention of the research community. IEEE 802.1 Time Sensitive Networking (TSN) task group targets the standardization of Ethernet-based deterministic communication technologies due to its high bandwidth and low cost. IEEE P802.1DG working group specifies the profile for secure and real-time automotive embedded systems relying on TSN, which is envisioned to be widely used in future in-vehicle platforms. In this paper, we present an elaborate review of the research work on the security of in-vehicle communication networks with TSN support, and define various Denial of Service (DoS) attack scenarios targeting the real-time traffic in in-vehicle networks. We evaluate the impact of our attack scenarios on the performance of two different realistic in-vehicle communication networks with varying sizes. Experimental results show that DoS attacks can lead to severe consequences disrupting the healthy operation of safety-critical functions in a TSN-compliant in-vehicle network.

A Systematic Review on Security Attacks and Countermeasures in Automotive Ethernet

In the past years, the automotive industry has experienced a technological revolution driven by the increasing demand of connectivity and data to develop driver-assistance systems and autonomous vehicles, and improve the mobility experience. To provide higher bandwidth in in-vehicle communication networks, carmakers are choosing Ethernet technology, which becomes Automotive Ethernet (AE) when applied in in-vehicle communication networks. However, with the rise of vehicle connectivity, the cybersecurity of vehicle systems has become a primary concern for the automotive industry. To address this issue, we conducted a systematic review, deeply analyzing the impact of AE on security and safety, and comparing it with the current in-vehicle communication solutions like Controller Area Network protocol. We retrieved the key security attacks and mitigations proposed in the current literature to highlight their significance, including a mapping between the regulation UNECE WP.29 R155 and the retrieved answers. We found that the industry has only implemented some automotive-dedicated Ethernet solutions to date. In the near future, the vehicle and road ecosystems may require more exclusive automotive solutions to meet specific constraints such as low latency. Our results can provide a comprehensive baseline, both for industry and academia, for the current and future development of AE.

In-Vehicle Data Communication with CAN &Security Monitoring: A Review

Automobiles are now being created with more electronic components for efficient functioning such as Anti Lock Braking system, Adaptive Cruise Control, Traction control system, Airbag, Power Steering etc. managed by networked controllers that include hundreds of ECUs (electronic control units) that can coordinate, control, and monitor loads of internal vehicle components. Each component, such as ABS, TCS (Traction control system), tire pressure monitoring system and telematics system, may communicate with nearby components over the CAN (Controller Area Network) bus, establishing an in-vehicle communication network. These modern automobile system networks intended for safety with minimal consideration for security have drawn the attention of researchers for providing security in CAN. The Paper reviews the behavior and vulnerabilities of CAN within an in-vehicle network including various attacks possible in CAN along with the proposed solutions in the literature with extensive survey on a security promising approach named as IDS (Intrusion detection system).

Enhancing Data Security in Autonomous Vehicle Communication Networks

In today's driving landscape, in-vehicle communication has become a cornerstone, facilitated by the proliferation of sensor-centric communication and computing devices within vehicles. These systems serve various functions such as vehicle monitoring, reducing physical wiring, and enhancing driving efficiency. However, the existing literature on cybersecurity for in-vehicle communication systems lacks dedicated solutions to mitigate in-vehicle cyber risks effectively. Current approaches primarily rely on protocol-specific security techniques, lacking a comprehensive security framework for in-vehicle communication. This paper critically examines the literature on cybersecurity for in-vehicle communication, focusing on technical architecture, methodologies, challenges, and potential solutions.
 The paper presents an in-depth analysis of in-vehicle communication network architecture, outlining key components, interfaces, and associated technologies. Protocols utilized in in-vehicle communication are classified based on their characteristics and usage types. Furthermore, security solutions for in-vehicle communication are critically reviewed, encompassing machine learning, cryptography, and port-centric techniques. A multi-layer secure framework is proposed as a protocol and use case-independent solution for in-vehicle communication security.Lastly, the paper identifies open challenges and outlines future research directions for enhancing cybersecurity in in-vehicle communication.

Event-triggered controller design for active suspension systems: An adaptive backstepping method with error-dependent gain

This paper studies an adaptive control problem for active suspension systems (ASSs) with parameter uncertainties based on the event-triggered mechanism (ETM). The main focus of this work is to improve the transient response of the body and save the communication resources of the in-vehicle network. The controller area network (CAN) is the most widely utilized in-vehicle communication network in automotive systems, so it is a vital issue that how to improve the utilization of the CAN resources since the CAN has a low bandwidth as a shared media. To this end, we present two error-dependent fixed and relative threshold ETMs to achieve satisfactory suspension performance while significantly reducing the communication burden on the CAN. Then, in the recursive design process, the backstepping strategy with error-dependent gain is employed to improve the transient response of the systems. Meanwhile, the radial basis function neural networks are adopted to identify the unknown nonlinearities in ASSs. Finally, the developed adaptive control algorithm ensures that all the signals in the closed-loop suspension systems are bounded in presence of uncertainties. Simulation results based on the professional vehicle simulation software Carsim verify the effectiveness of the presented scheme.

Event-Triggered Adaptive Finite-Time Control for Active Suspension Systems With Prescribed Performance

In this article, we address the event-triggered based adaptive finite-time control problem for active suspension systems (ASSs) over the resource-constrained controller area network (CAN), which is the most extensively employed in-vehicle communication network in automotive systems. The control aim is to develop an event-triggered algorithm to reduce the communication burden from the CAN and meanwhile improve the suspension performances. Specifically, a novel finite-time performance function is presented to guarantee that the tracking error is retained in a small region at any prespecified time. It is shown that under the proposed control framework, ride comfort, suspension space limitation, and handling stability are all ensured. Then, the established event-triggered mechanism based on the relative threshold method can avoid Zeno behavior. Finally, all the signals are bounded for the closed-loop ASSs. The usefulness of the presented adaptive control strategy is demonstrated through the simulation results.

Secure over-the-air software update for connected vehicles

Current trends forecast that Over-the-Air (OTA) software updates will be highly significant for future connected vehicles. The OTA software updates will enable upgrading vehicle functionalities or bug fixations in embedded software installed on electronic control units remotely. However, in terms of security, OTA updates are highly critical as they need complete access to the in-vehicle communication network. Furthermore, scheduling OTA software updates at a massive scale over a cellular network is highly challenging. This paper proposes STRIDE, a novel technique for secure and scalable software updates using cloud through cellular network. STRIDE ensures end-to-end security using ciphertext-policy attribute-based encryption. To enable fast and reliable distribution of update package, we then propose a software update scheduling algorithm to serve dynamic traffic flow. Particularly, we integrate dynamic traffic flow with the Lyapunov-drift analysis framework, and establish throughput optimality of our proposed scheduling algorithm. We evaluate the performance of STRIDE through extensive experiments. Experimental results show that STRIDE reduces more than 52% computation and storage overheads, 60% propagation delay and increases throughput by 35% than the state-of-the-art solutions, in addition to enjoying the stronger security properties.

In-Vehicle Communication Cyber Security: Challenges and Solutions.

In-vehicle communication has become an integral part of today’s driving environment considering the growing add-ons of sensor-centric communication and computing devices inside a vehicle for a range of purposes including vehicle monitoring, physical wiring reduction, and driving efficiency. However, related literature on cyber security for in-vehicle communication systems is still lacking potential dedicated solutions for in-vehicle cyber risks. Existing solutions are mainly relying on protocol-specific security techniques and lacking an overall security framework for in-vehicle communication. In this context, this paper critically explores the literature on cyber security for in-vehicle communication focusing on technical architecture, methodologies, challenges, and possible solutions. In-vehicle communication network architecture is presented considering key components, interfaces, and related technologies. The protocols for in-vehicle communication have been classified based on their characteristics, and usage type. Security solutions for in-vehicle communication have been critically reviewed considering machine learning, cryptography, and port-centric techniques. A multi-layer secure framework is also developed as a protocol and use case-independent in-vehicle communication solution. Finally, open challenges and future dimensions of research for in-vehicle communication cyber security are highlighted as observations and recommendations.

Delay-Aware Multi-Layer Multi-Rate Model Predictive Control for Vehicle Platooning Under Message-Rate Congestion Control

Vehicle platooning is an enabler technology for increasing road capacity, improving safety and reducing fuel consumption. Platoon control is a two-layered system where each layer runs under a different communication standard and rate – (i) the upper-layer operates under a specific V2V communication standard such as IEEE 802.11p and (ii) the lower-layer operates over high-speed in-vehicle communication networks such as FlexRay, CAN. The upper-layer, under 802.11p, uses periodic Cooperative Awareness Messages (CAMs) for exchanging vehicle motion information (i.e., acceleration, velocity and so on), the rate of which is adapted depending on the network congestion level. With over 70% channel load, the CAMs experience significant delay and packet loss, jeopardizing the stability of the platoon control. Under such high congestion, the European Telecommunications Standard Institute (ETSI) proposes to engage Decentralized Congestion Control (DCC) to control the channel load. We propose a platoon control and DCC scheme to tackle this scenario. Our contribution is three-fold. First, we propose a multi-layer platoon model explicitly augmenting the communication delay in the state-space. Second, the augmented delay-aware platoon model is integrated in the state-of-the-art multi-layer multi-rate model predictive control (MPC) for the upper-layer. Third, we adopt a message-rate congestion control scheme to keep the channel load under a given threshold. We use the proposed delay-aware MPC scheme under the message-rate congestion control scheme which may lead to switching under dynamic network conditions. Using the proposed technique, we show that platoon performance can be maintained under high network congestion while maintaining string stability.

Analysis of Security Vulnerability Levels of In-Vehicle Network Topologies Applying Graph Representations

This article investigates cybersecurity issues related to in-vehicle communication networks. In-vehicle communication network security is evaluated based on the protection characteristics of the network components and the topology of the network. The automotive communication network topologies are represented as undirected weighted graphs, and their vulnerability is estimated based on the specific characteristics of the generated graph. Thirteen different vehicle models have been investigated to compare the vulnerability levels of the in-vehicle network using the Dijkstra's shortest route algorithm. An important advantage of the proposed method is that it is in accordance with the most relevant security evaluation models. On the other hand, the newly introduced approach considers the Secure-by-Design concept principles.

A Novel Vehicular Heatstroke Prevention by Smart HVAC System Model

Today, automobile safety has become one of the paramount focus areas by car manufacturers. The vehicles of today have increasingly grown more intelligent to keep passengers safe on the road. Apart from traffic safety, non-crash safety issues progressively turn out to be another prime concern. Currently, vehicular heatstroke deaths in parked vehicles are one of the major focuses in the non-crash safety domain. 2018 saw a total of 52 American children died while 90% out of 8290 calls to RSPCA concerned trapped dogs in scorching cars. Thus, we proposed a prototype system with the capability to monitor vehicle conditions and take appropriate actions to save a life. The objective of this work is to reduce the possibility of uninformed passengers, especially children, the elderly, and the pets, from unnecessary deaths or suffering from trapped car-related heatstroke. This prototype can be further enhanced to smartly communicate with other Electrical Control Units (ECUs) inside the vehicle via an in-vehicle communication network, i.e. CAN bus to further improve vehicle safety.

A Kohonen SOM Architecture for Intrusion Detection on In-Vehicle Communication Networks

The diffusion of connected devices in modern vehicles involves a lack in security of the in-vehicle communication networks such as the controller area network (CAN) bus. The CAN bus protocol does not provide security systems to counter cyber and physical attacks. Thus, an intrusion-detection system to identify attacks and anomalies on the CAN bus is desirable. In the present work, we propose a distance-based intrusion-detection network aimed at identifying attack messages injected on a CAN bus using a Kohonen self-organizing map (SOM) network. It is a power classifier that can be trained both as supervised and unsupervised learning. SOM found broad application in security issues, but was never performed on in-vehicle communication networks. We performed two approaches, first using a supervised X–Y fused Kohonen network (XYF) and then combining the XYF network with a K-means clustering algorithm (XYF–K) in order to improve the efficiency of the network. The models were tested on an open source dataset concerning data messages sent on a CAN bus 2.0B and containing large traffic volume with a low number of features and more than 2000 different attack types, sent totally at random. Despite the complex structure of the CAN bus dataset, the proposed architectures showed a high performance in the accuracy of the detection of attack messages.

Evaluation of CAN Bus Security Challenges.

The automobile industry no longer relies on pure mechanical systems; instead, it benefits from many smart features based on advanced embedded electronics. Although the rise in electronics and connectivity has improved comfort, functionality, and safe driving, it has also created new attack surfaces to penetrate the in-vehicle communication network, which was initially designed as a close loop system. For such applications, the Controller Area Network (CAN) is the most-widely used communication protocol, which still suffers from various security issues because of the lack of encryption and authentication. As a result, any malicious/hijacked node can cause catastrophic accidents and financial loss. This paper analyses the CAN bus comprehensively to provide an outlook on security concerns. It also presents the security vulnerabilities of the CAN and a state-of-the-art attack surface with cases of implemented attack scenarios and goes through different solutions that assist in attack prevention, mainly based on an intrusion detection system (IDS).

Velocity-based robust fault tolerant automatic steering control of autonomous ground vehicles via adaptive event triggered network communication

This paper proposes a velocity-based robust fault tolerant automatic steering control approach for autonomous ground vehicles via an adaptive event triggered network communication mechanism. Firstly, as the vehicle longitudinal velocity is not fixed but time-varying, a polytope with finite vertices is adopted to construct a linear parameter varying vehicle system model. Secondly, since network-induced delay and actuator fault inevitably occur in the control system, a novel Lyapunov function is formulated to guarantee the asymptotical stability of the closed-loop system. Moreover, an advanced event triggered communication scheme is proposed for the co-design of robust automatic steering controller, which is quite effective to reduce network communication burden and enhance resource utilization of the shared band-limited in-vehicle communication network. Finally, numerical simulations on two cases are carried out to evaluate and verify the effectiveness and robustness of the proposed controller. Compared with existing studies, the proposed controller contributes greatly to the economization of communication resource and improvement of path following performance and lateral stability.

Timing Analysis of Precedence Constraint Messages Scheduled With Slot Multiplexing Over Dynamic Segment of FlexRay

FlexRay offers high-speed reliable transmission in the vehicle domain. Thus, it is one of the most popular in-vehicle communication protocols for the applications that are safety-critical or applications with very low transmission time requirement. Due to the real-time constraint, the worst case end-to-end delay (EED) for such applications transmitting over a shared bus must be known. This paper addresses the problem of computation of EED for a given set of tasks with precedence constraint and corresponding messages, which are scheduled with slot multiplexing for event-triggered communication over the dynamic segment of FlexRay. First, computing precise delay has been shown to be an intractable problem. Subsequently, motivated by the intractability, an efficient estimation technique has been proposed to compute approximate EED. Unlike the common practice of considering the network in isolation, we present a comprehensive timing analysis, which considers the effects of task execution as well. Moreover, EED is allowed to be greater than interactivation time of task graph. The extensive simulation has been performed on the test cases generated with uniform as well as normal distribution. Note to Practitioners —In the past few decades, due to the large-scale use and sophistication of automotive electronic systems, various in-vehicle communication networks and protocols are also evolving. FlexRay is one such in-vehicle communication protocol, which provides the mechanism for the fault-tolerant high-speed communication over FlexRay bus. FlexRay is widely being employed for safety-critical applications in the automotive domain. For such applications, often the timing constraint is imposed with a bound on the worst case EED. Thus, timing properties of the designed network must be verified before applying it on the real domain such that the worst case EED for the propagation of an event at sensor end to actuator end is known. The proposed estimation technique can be used to compute approximate EED for an application scheduled with other applications over the dynamic segment of FlexRay. In addition, various guidelines for designing the network in order to reduce overestimation have also been presented.

Research of Message Scheduling for In-Vehicle FlexRay Network Static Segment Based on Next Fit Decreasing (NFD) Algorithm

FlexRay is becoming the in-vehicle communication network of the next generation. In this study, the main contents are the FlexRay network static segment scheduling algorithm and optimization strategy, improve the scheduling efficiency of vehicle network and optimize the performance of communication network. The FlexRay static segment characteristic was first analyzed, then selected bandwidth utilization as the performance metrics to scheduling problem. A signal packing method is proposed based on Next Fit Decreasing (NFD) algorithm. Then Frame ID (FID) multiplexing method was used to minimize the number of FIDs. Finally, experimental simulation by CANoe. FlexRay software, that shows the model can quickly obtain the message schedule of each node, effectively control the message payload size and reduced bus payload by 16.3%, the number of FID drops 53.8% while improving bandwidth utilization by 32.8%.

Implementation of an Integrated Controller for a Robot Hand Base on a Vehicle Communication System

Intelligent robots commonly adopt Network-Based Control Systems (NBCS). For control of a robot hand or a robot head, many sensor data and control commands need to be transmitted in real time, so they have necessitated communication systems with high transmission capability. Traditionally, CAN is widely used for intelligent robots, but it presents bandwidths that are too low for the control of a high performance system. In this paper, the relation between the transmission period and the performance of a multi-motor control system is analyzed, and a multi-motor control system for a human robot hand is implemented based on the FlexRay communication system, which is an emerging in-vehicle communication network system. FlexRay parameter optimization for a robot system is studied, and a real position control test is conducted, to validate the implemented system.