Availability evaluation of controller area networks under the influence of intermittent connection faults

Controller area networks(CANs),as one of the widely used fieldbuses in the industry,have been extended to the automation field with strict standards for safety and reliability.In practice,factors such as fatigue and insulation wear of the cables can cause intermittent connection(IC)faults to occur frequently in the CAN,which will affect the dynamic behavior and the safety of the system.Hence,quantitatively evaluating the performance of the CAN under the influence of IC faults is crucial to real-time health monitoring of the system.In this paper,a novel methodology is proposed for real-time quantitative evaluation of CAN availability when considering IC faults,with the system availability parameter being calculated based on the network state transition model.First,the causal relationship between IC fault and network error response is constructed,based on which the IC fault arrival rate is estimated.Second,the states of the network considering IC faults are analyzed,and the deterministic and stochastic Petri net(DSPN)model is applied to describe the transition relationship of the states.Then,the parameters of the DSPN model are determined and the availability of the system is calculated based on the probability distribution and physical meaning of markings in the DSPN model.A testbed is constructed and case studies are conducted to verify the proposed methodology under various experimental setups.Experimental results show that the estimation results obtained using the proposed method agree well with the actual values.

Controller area network node reliability assessment based on observable node information

Controller area network(CAN) based fieldbus technologies have been widely used in networked manufacturing systems. As the information channel of the system, the reliability of the network is crucial to the system throughput, product quality, and work crew safety. However, due to the inaccessibility of the nodes' internal states, direct assessment of the reliability of CAN nodes using the nodes' internal error counters is infeasible. In this paper, a novel CAN node reliability assessment method, which uses node's time to bus-off as the reliability measure, is proposed. The method estimates the transmit error counter(TEC) of any node in the network based on the network error log and the information provided by the observable nodes whose error counters are accessible.First, a node TEC estimation model is established based on segmented Markov chains. It considers the sparseness of the distribution of the CAN network errors. Second, by learning the differences between the model estimates and the actual values from the observable node, a Bayesian network is developed for the estimation updating mechanism of the observable nodes. Then, this estimation updating mechanism is transferred to general CAN nodes with no TEC value accessibility to update the TEC estimation. Finally, a node reliability assessment method is developed to predict the time to reach bus-off state of the nodes. Case studies are carried out to demonstrate the effectiveness of the proposed methodology. Experimental results show that the estimates using the proposed model agree well with actual observations.

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

A Comprehensive Analysis of Datasets for Automotive Intrusion Detection Systems

Recently,automotive intrusion detection systems(IDSs)have emerged as promising defense approaches to counter attacks on in-vehicle networks(IVNs).However,the effectiveness of IDSs relies heavily on the quality of the datasets used for training and evaluation.Despite the availability of several datasets for automotive IDSs,there has been a lack of comprehensive analysis focusing on assessing these datasets.This paper aims to address the need for dataset assessment in the context of automotive IDSs.It proposes qualitative and quantitative metrics that are independent of specific automotive IDSs,to evaluate the quality of datasets.These metrics take into consideration various aspects such as dataset description,collection environment,and attack complexity.This paper evaluates eight commonly used datasets for automotive IDSs using the proposed metrics.The evaluation reveals biases in the datasets,particularly in terms of limited contexts and lack of diversity.Additionally,it highlights that the attacks in the datasets were mostly injected without considering normal behaviors,which poses challenges for training and evaluating machine learning-based IDSs.This paper emphasizes the importance of addressing the identified limitations in existing datasets to improve the performance and adaptability of automotive IDSs.The proposed metrics can serve as valuable guidelines for researchers and practitioners in selecting and constructing high-quality datasets for automotive security applications.Finally,this paper presents the requirements for high-quality datasets,including the need for representativeness,diversity,and balance.

FIDS:Filtering-Based Intrusion Detection System for In-Vehicle CAN

Modern vehicles are equipped with multiple Electronic Control Units(ECUs)that support various convenient driving functions,such as the Advanced Driver Assistance System(ADAS).To enable communication between these ECUs,the Controller Area Network(CAN)protocol is widely used.However,since CAN lacks any security technologies,it is vulnerable to cyber attacks.To address this,researchers have conducted studies on machine learning-based intrusion detection systems(IDSs)for CAN.However,most existing IDSs still have non-negligible detection errors.In this paper,we pro-pose a new filtering-based intrusion detection system(FIDS)to minimize the detection errors of machine learning-based IDSs.FIDS uses a whitelist and a blacklist created from CAN datasets.The whitelist stores the cryptographic hash value of normal packet sequences to correct false positives(FP),while the blacklist corrects false negatives(FN)based on transmission intervals and identifiers of CAN packets.We evaluated the performance of the proposed FIDS by implementing a machine learning-based IDS and applying FIDS to it.We conducted the evaluation using two CAN attack datasets provided by the Hacking and Countermeasure Research Lab(HCRL),which confirmed that FIDS can effectively reduce the FP and FN of the existing IDS.

Data Driven CAN Node Reliability Assessment for Manufacturing System

The reliability of the Controller Area Network（CAN） is critical to the performance and safety of the system. However, direct bus-off time assessment tools are lacking in practice due to inaccessibility of the node information and the complexity of the node interactions upon errors. In order to measure the mean time to bus-off（MTTB） of all the nodes, a novel data driven node bus-off time assessment method for CAN network is proposed by directly using network error information. First, the corresponding network error event sequence for each node is constructed using multiple-layer network error information. Then, the generalized zero inflated Poisson process（GZIP） model is established for each node based on the error event sequence. Finally, the stochastic model is constructed to predict the MTTB of the node. The accelerated case studies with different error injection rates are conducted on a laboratory network to demonstrate the proposed method, where the network errors are generated by a computer controlled error injection system. Experiment results show that the MTTB of nodes predicted by the proposed method agree well with observations in the case studies. The proposed data driven node time to bus-off assessment method for CAN networks can successfully predict the MTTB of nodes by directly using network error event data.

Cascaded Multilevel Inverter Based Power and Signal Multiplex Transmission for Electric Vehicles

Power&signal multiplex transmission(P&SMT)is a technique that uses power electronic circuits for communication signal transmission.In this paper,a three-phase cascaded multilevel inverter-based P&S MT system is proposed.The proposed method can transmit communication signals without using a Controller Area Network bus,thereby reducing the wiring cost of the conventional electric vehicle(EV)communication system.The designed system can achieve motor speed regulation and battery balance discharging for EVs.With the combined pulse width modulation scheme and frequency shift keying method,both power and communication signals are transmitted successfully in a simulation model implemented in Matlab/Simulink.By evaluating the bit error rate of the transmitted signal,the maximum signal rate of the proposed system is determined as 600 bit/s.

MULTIPLE ELECTRONIC CONTROL UNITS CALIBRATION SYSTEM BASED ON EXPLICIT CALIBRATION PROTOCOL AND J1939 PROTOCOL

The rising number of electronic control units （ECUs） in vehicles and the decreasing time to market have led to the need for advanced methods of calibration. A multi-ECU calibration system was developed based on the explicit calibration protocol （XCP） and J1939 communication protocol to satisfy the need of calibrating multiple ECUs simultaneously. The messages in the controller area network （CAN） are defined in the J1939 protocol. Each CAN node can get its own calibration messages and information from other ECUs, and block other messages by qualifying the CAN messages with priority, source or destination address. The data field of the calibration message is designed with the XCP, with CAN acting as the transport layer. The calibration sessions are setup with the event-triggered XCP driver in the master node and the responding XCP driver in the slave nodes. Mirroring calibration variables from ROM to RAM enables the user to calibrate ECUs online. The application example shows that the multi-ECU calibration system can calibrate multiple ECUs simultaneously, and the main program can also accomplish its calculation and send commands to the actuators in time. By the multi-ECU calibration system, the calibration effort and time can be reduced and the variables in ECU can get a better match with the variables of other ECUs.

Development of a Robot for In-service Radiography Inspection of Subsea Flexible Risers

The extreme operational environmental conditions and aging conditions of subsea structures pose a risk to their structural integrity and is critical to their safety.Nondestructive testing is essential to identify defects developing within the structure,allowing repair in a timely manner to mitigate against failures that cause damage to the environment and pose a hazard to human operators.However,to be cost effective,inspections must be carried out without taking the risers out of service.This poses significant safety risks if undertaken manually.This paper presents the development of an automated inspection system for flexible risers that are used to connect wellheads on the seafloor to the offshore production and storage facility.Due to the complex structure of risers,radiography is considered as the best technique to inspect multiple layers of the risers.However,radiography inspection,in turn,requires a robotic system for in-situ inspection with higher payload capacity,precise movement of source and detector which is able to withstand an extreme operational environment.The deployment of a radiography inspection system hasbeen achieved bydeveloping acustomized subsearobotic system called RiserSure that can provide precise scanning motion of a gamma ray source and digital detector moving in alignment.The prototype has been tested on a flexible riser during shallow water sea trials with the system placed around a riser by a remotely operated vehicle.The results from the trials show that the internal inner and outer tensile armor layer and defects in the riser can be successfully imaged in real operational conditions.

An Approach for Damage Identification and Optimal Sensor Placement in Structural Health Monitoring by Genetic Algorithm Technique

Civil engineering structures are constructed for strength, serviceability and durability. The structures thus constructed involve huge investment and labour work. In order to protect the structure from various damages, periodic monitoring of structures is necessary. Hence Structural Health Monitoring (SHM) plays a vital role in diagnosing the state of the structure at every moment during its life period. For this purpose, sensors are deployed in the structures for its efficient health monitoring. Sensors cannot be deployed at random locations of the structure. They have to be located at those points which reflect the damage. In this study, a 3-storey and a 4-storey building are taken and Modal Strain Energy (MSE) is used for finding the initial locations of sensors. The number of sensors obtained is then optimized using Genetic Algorithm (GA) technique. Finally damages are induced in certain locations of the structure and a damage detection technique called as “Flexibility Matrix Based Technique (FMBT)” is introduced for damage localization in the structure.

Control and Communication Network in Hybrid Fuel Cell Vehicles

This paper describes the control and communication network in fuel cell vehicles, including both the protocol and the hardware. Based on the current protocol (ISO-11898 and SAE J1939), a new practical protocol is proposed and implemented for the control and communication network in fuel cell vehicles. To improve the re-liability of data communication and to unify the network management, a new network system based on dual-port RAM is also implemented.

Embedded software and hardware implementation system for a human machine interface based on ISOAgLib

Modern agricultural machinery demands adoption of embedded electronic and remote sensing technology for precision agriculture.One of the electronic devices commonly used is the virtual terminal(VT) for tractors.A VT's functions and terminology are described in the ISO 11783 standard.This paper presents a control system design and implementation for a VT and some other electronic control units(ECUs) for agricultural vehicles based on that standard.Hardware and software development for the VT is implemented using the ISOAgLib open library,in the advanced embedded system.The main part of the system is an embedded board based on a Samsung S3C6410 ARM11 core microprocessor with a controller area network(CAN) module.Its working environment is Windows Embedded CE 6.0(WinCE6.0).The ISOAgLib library provides abundant open sources consistent implementation of ISO 11783.It is written in C++ programming language using object-oriented technology.In this paper,we describe an ISO 11783-based tractor control system with a CAN and its implementation in the embedded system.This paper also explains the operation of a CAN-bus device driver in WinCE6.0 and some modifications of ISOAgLib for our target system.The target system consists of the VT,an ECU for the global positioning system(GPS),and an ECU for lighting for an agricultural tractor.The ECU for GPS and the ECU of a light controller are implemented using STM32F107F ARM Cortex M3-based development boards.

浅谈汽车控制模块中的动力CAN接口芯片电路

汽车控制模块中的CAN接口芯片属于易损件,所以深入了解CAN接口芯片及其电路对于汽车控制模块的维修具有重要意义。1CAN总线CAN是英文Controller Area Network的缩写,中文意思为控制器(控制模块)局域网络,由于消费者对汽车功能需求的不断增加。