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The overview of public key infrastructure based security approaches for vehicular communications
(2015)
Modern transport infrastructure becomes a full member of globally connected network. Leading vehicle manufacturers have already triggered development process, output of which will open a new horizon of possibilities for consumers and developers by providing a new communication entity - a car, thus enabling Car2X communications. Nevertheless some of available systems already provide certain possibilities for vehicles to communicate, most of them are considered not sufficiently secured. During last 15 years a number of big research projects funded by European Union and USA governments were started and concluded after which a set of standards were published prescribing a common architecture for Car2X and vehicles onboard communications. This work concentrates on combining inner and outer vehicular communications together with a use of Public Key Infrastructure (PKI).
Wireless communication systems more and more become part of our daily live. Especially with the Internet of Things (IoT) the overall connectivity increases rapidly since everyday objects become part of the global network. For this purpose several new wireless protocols have arisen, whereas 6LoWPAN (IPv6 over Low power Wireless Personal Area Networks) can be seen as one of the most important protocols within this sector. Originally designed on top of the IEEE802.15.4 standard it is a subject to various adaptions that will allow to use 6LoWPAN over different technologies; e.g. DECT Ultra Low Energy (ULE). Although this high connectivity offers a lot of new possibilities, there are several requirements and pitfalls coming along with such new systems. With an increasing number of connected devices the interoperability between different providers is one of the biggest challenges, which makes it necessary to verify the functionality and stability of the devices and the network. Therefore testing becomes one of the key components that decides on success or failure of such a system. Although there are several protocol implementations commonly available; e.g., for IoT based systems, there is still a lack of according tools and environments as well as for functional and conformance testing. This article describes the architecture and functioning of the proposed test framework based on Testing and Test Control Notation Version 3 (TTCN-3) for 6LoWPAN over ULE networks.
The CAN bus still is an important fieldbus in various domains, e.g. for in-car communication or automation applications. To counter security threats and concerns in such scenarios we design, implement, and evaluate the use of an end-to-end security concept based on the Transport Layer Security protocol. It is used to establish authenticated, integrity-checked, and confidential communication channels between field devices connected via CAN. Our performance measurements show that it is possible to use TLS at least for non time-critical applications, as well as for generic embedded networks.
Objective: Dickkopf 3 (DKK3) has been identified as a urinary biomarker. Values above 4000 pg/mg creatinine (Cr) were linked with a higher risk of short-term decline of kidney function (J Am Soc Nephrol 29: 2722–2733). However, as of today, there is little experience with DKK3 as a risk marker in everyday clinical practice. We used algorithm-based data analysis to evaluate the potential dependence of DKK3 in a cohort from a large single center in Germany.
Method: DKK3 was measured in all CKD patients in our center October 1 st 2018 till Dec. 31 2019, together with calculated GFR (eGFR) and urinary albumin/creatinine ratio (UACR). Kidney transplant patients were excluded. Until the end of follow-up Dec 31 st 2021, repeated measurements were performed for all parameters. Data analysis was performed using MD-Explorer (BioArtProducts, Rostock, Germany) and Python with multiple libraries. Linear regression models were applied in patients for DKK3, eGFR and UACR. Comparison of the models was performed with a twosided Kolmogorov-Smirnov test.
Results: 1206 DKK3 measurements were performed in 1103 patients (621 male, age 70yrs, eGFR 29,41 ml/min/1.73qm, UACR 800 mg/g). 134 patients died during follow-up. DKK3 mean was 2905 pg/mg Cr (max. 20000, 75 % percentile 3800). 121 pts had DKK3 > 4000. At the end of follow-up 7 % of patients with DKK3 < 4000 (initial eGFR 17.6) versus 39.6 % of patients with DDK3 > 4000 (initial eGFR 15.7) underwent dialysis. Compared to eGFR and UACR at baseline, DKK3 > 4000 performed best to predict eGFR loss over the next 12 months.
Conclusion: In this cohort of CKD patients, DKK3 > 4000 at baseline predicted the eGFR slope better than eGFR or UACR at baseline. DKK3 > 4000 reflected a higher risk of progression towards ESRD in patients with similar baseline eGFR levels.
Security in IT systems, particularly in embedded devices like Cyber Physical Systems (CPSs), has become an important matter of concern as it is the prerequisite for ensuring privacy and safety. Among a multitude of existing security measures, the Transport Layer Security (TLS) protocol family offers mature and standardized means for establishing secure communication channels over insecure transport media. In the context of classical IT infrastructure, its security with regard to protocol and implementation attacks has been subject to extensive research. As TLS protocols find their way into embedded environments, we consider the security and robustness of implementations of these protocols specifically in the light of the peculiarities of embedded systems. We present an approach for systematically checking the security and robustness of such implementations using fuzzing techniques and differential testing. In spite of its origin in testing TLS implementations we expect our approach to likewise be applicable to implementations of other cryptographic protocols with moderate efforts.
The Thread protocol is a recent development based on 6LoWPAN (IPv6 over IEEE 802.15.4), but with extensions regarding a more media independent approach, which – additionally – also promises true interoperability. To evaluate and analyse the operation of a Thread network a given open source 6LoWPAN stack for embedded devices (emb::6) has been extended in order to comply with the Thread specification. The implementation covers Mesh Link Establishment (MLE) and network layer functionality as well as 6LoWPAN mesh under routing mechanism based on MAC short addresses. The development has been verified on a virtualization platform and allows dynamical establishment of network topologies based on Thread's partitioning algorithm.
OPC UA (Open Platform Communications Unified Architecture) is already a well-known concept used widely in the automation industry. In the area of factory automation, OPC UA models the underlying field devices such as sensors and actuators in an OPC UA server to allow connecting OPC UA clients to access device-specific information via a standardized information model. One of the requirements of the OPC UA server to represent field device data using its information model is to have advanced knowledge about the properties of the field devices in the form of device descriptions. The international standard IEC 61804 specifies EDDL (Electronic Device Description Language) as a generic language for describing the properties of field devices. In this paper, the authors describe a possibility to dynamically map and integrate field device descriptions based on EDDL into OPCUA.
The IEEE802.11p standard describes a protocol for car-to-X and mainly for car-to-car-communication. It has found its place in hardware and firmware implementations and is currently tested in various field tests. In the research project Ko-TAG, which is part of the research initiative Ko-FAS, cooperative sensor technology is developed and its benefit for traffic safety applications is evaluated. A secondary radar principle based on communication signals enables localization of objects with simultaneous data transmission. It mainly concentrates on the detection of pedestrians and other vulnerable road users (VRU), but also supports pre crash safety applications. The Ko-TAG proposal enriches the current IEEE802.11p real-time characteristics needed for precise time-of-flight real-time localization. This contribution describes the development of a subsystem, which extends the functionality of IEEE802.11p and fits into the regulatory schemes. It discusses the approach for definition and verification of the protocol design, while maintaining the close coexistence with existing IEEE802.11p subsystems. System simulations were performed and hardware was implemented. The next step will be field measurements to verify the simulation results.
Die neueste Generation von programmierbaren Logikbausteinen verfügt neben den konfigurierbaren Logikzellen über einen oder mehrere leistungsfähige Mikroprozessoren. In dieser Arbeit wird gezeigt, wie ein bestehendes Zwei-Chip-System auf einen Xilinx Zynq 7000 mit zwei ARM A9-Cores migriert wird. Bei dem System handelt es sich um das „GPS-gestützte Kreisel-system ADMA“ des Unternehmens GeneSys. Die neue Lösung verbessert den Datenaustausch zwischen dem ersten Mikroprozessor zur digitalen Signalverarbeitung und dem zweiten Prozessor zur Ablaufsteuerung durch ein Shared Memory. Für die schnelle und echtzeitfähige Datenübertragung werden zahlreiche hochbitratige Schnittstellengenutzt.
Legacy industrial communication protocols are proved robust and functional. During the last decades, the industry has invented completely new or advanced versions of the legacy communication solutions. However, even with the high adoption rate of these new solutions, still the majority industry applications run on legacy, mostly fieldbus related technologies. Profibus is one of those technologies that still keep on growing in the market, albeit a slow in market growth in recent years. A retrofit technology that would enable these technologies to connect to the Internet of Things, utilize the ever growing potential of data analysis, predictive maintenance or cloud-based application, while at the same time not changing a running system is fundamental.
The research project Ko-TAG [2], as part of the research initiative Ko-FAS [1], funded by the German Ministry of Economics and Technologies (BMWi), deals with the development of a wireless cooperative sensor system that shall pro-vide a benefit to current driver assistance systems (DAS) and traffic safety applications (TSA). The system’s primary function is the localization of vulnerable road users (VRU) e.g. pedestrians and powered two-wheelers, using communication signals, but can also serve as pre-crash (surround) safety system among vehicles. The main difference of this project, compared to previous ones that dealt with this topic, e.g. the AMULETT project, is an underlying FPGA based Hardware-Software co-design. The platform drives a real-time capable communication protocol that enables highly scalable network topologies fulfilling the hard real-time requirements of the single localization processes. Additionally it allows the exchange of further data (e.g. sensor data) to support the accident pre-diction process and the channel arbitration, and thus supports true cooperative sensing. This paper gives an overview of the project’s current system design as well as of the implementations of the key HDL entities supporting the software parts of the communication protocol. Furthermore, an approach for the dynamic reconfiguration of the devices is described, which provides several topology setups using a single PCB design.
Energy and environment continue to be major issues of human mankind. This holds true on the regional, the national, and the global level. And it is one of the problems, where engineers and scientists in conjunction with political will and people's awareness, can find new approaches and solutions to save the natural resources and to make their use more efficient.
Institute of Reliable Embedded Systems and Communication Electronics, Offenburg University of Applied Sciences, Germany has developed an automated testing environment, Automated Physical TestBeds (APTB), for analyzing the performance of wireless systems and its supporting protocols. Wireless physical networking nodes can connect to this APTB and the antenna output of this attaches with the RF waveguides. To model the RF environment this RF waveguides then establish wired connection among RF elements like splitters, attenuators and switches. In such kind of set up it’s well possible to vary the path characteristics by altering the attenuators and switches. The major advantage of using APTB is the possibility of isolated, well controlled, repeatable test environment in various conditions to run statistical analysis and even to execute regression tests. This paper provides an overview of the design and implementation of APTB, demonstrates its ability to automate test cases, and its efficiency.
Automatic Meter Reading (AMR) is a major enabler for the upcoming smart grid. Potentially, it will be one of the first really large-scale M2M-communication solutions for sensor applications.
To date, the definition of the standardized communication stacks for Local Metrological Network (LMN) in AMR is still ongoing. This holds true both for ZigBee Smart Energy Profile and for Wireless M-Bus according to EN 13757. During this process, there is the necessity for flexible, albeit optimized solutions, which support the different existing and upcoming versions of the communication protocols. In the case of Wireless M-Bus, the major contender for European and possibly Asian installations, this is valid not only for the different operation modes (C-, N-, P-, Q-, R-, S-, and T-modes), which work in different frequencies (i.e. 868 MHz, 433 MHz, and 169 MHz) but also for the application layer, where additional bodies, like EN137575, Open Metering System (OMS) Group, or national bodies follow their approaches.
This contribution describes requirements, design techniques and experiences from the development of highly efficient Wireless M-Bus protocol stacks with support of good flexibility and portability between microcontroller platforms and RF-transceivers. The presented approach is not limited to the use of modern software engineering design processes, as such, but also includes essential additional features like testing or simulation, as well as tools for commissioning and monitoring.
The Internet of Things (IoT), ubiquitous computing and ubiquitous connectivity, Cyber Physical Systems (CPS), ambient intelligence, Machine-to-Machine communication (M2M) or Car-to-Car (C2C)-communication, smart metering, smart grid, telematics, telecare, telehealth – there are many buzzwords around current developments related to the Internet.
This contribution gives an overview on such IoT-applications, as they are already used today to improve the availability of information, increase efficiency, push system limits and extend the value chain. At a closer look, the economic and technical development can be separated into different phases. It is interesting that we are currently at the threshold to a new phase, with decentralized and cooperative communication and control nodes as cornerstones. Thus, embedded systems and their connectivity are in the middle of the scene.
This recent development is described along with some example projects from the author’s team which are used in industrial automation, energy supply and distribution (home automation and smart metering), traffic engineering (cooperative driver assistance systems), and in telehealth and telecare.
To demonstrate how deep learning can be applied to industrial applications with limited training data, deep learning methodologies are used in three different applications. In this paper, we perform unsupervised deep learning utilizing variational autoencoders and demonstrate that federated learning is a communication efficient concept for machine learning that protects data privacy. As an example, variational autoencoders are utilized to cluster and visualize data from a microelectromechanical systems foundry. Federated learning is used in a predictive maintenance scenario using the C-MAPSS dataset.
In recent years, the topic of embedded machine learning has become very popular in AI research. With the help of various compression techniques such as pruning, quantization and others compression techniques, it became possible to run neural networks on embedded devices. These techniques have opened up a whole new application area for machine learning. They range from smart products such as voice assistants to smart sensors that are needed in robotics. Despite the achievements in embedded machine learning, efficient algorithms for training neural networks in constrained domains are still lacking. Training on embedded devices will open up further fields of applications. Efficient training algorithms would enable federated learning on embedded devices, in which the data remains where it was collected, or retraining of neural networks in different domains. In this paper, we summarize techniques that make training on embedded devices possible. We first describe the need and requirements for such algorithms. Then we examine existing techniques that address training in resource-constrained environments as well as techniques that are also suitable for training on embedded devices, such as incremental learning. At the end, we also discuss which problems and open questions still need to be solved in these areas.
Training deep neural networks using backpropagation is very memory and computationally intensive. This makes it difficult to run on-device learning or fine-tune neural networks on tiny, embedded devices such as low-power micro-controller units (MCUs). Sparse backpropagation algorithms try to reduce the computational load of on-device learning by training only a subset of the weights and biases. Existing approaches use a static number of weights to train. A poor choice of this so-called backpropagation ratio limits either the computational gain or can lead to severe accuracy losses. In this paper we present TinyProp, the first sparse backpropagation method that dynamically adapts the back-propagation ratio during on-device training for each training step. TinyProp induces a small calculation overhead to sort the elements of the gradient, which does not significantly impact the computational gains. TinyProp works particularly well on fine-tuning trained networks on MCUs, which is a typical use case for embedded applications. For typical datasets from three datasets MNIST, DCASE2020 and CIFAR10, we are 5 times faster compared to non-sparse training with an accuracy loss of on average 1%. On average, TinyProp is 2.9 times faster than existing, static sparse backpropagation algorithms and the accuracy loss is reduced on average by 6 % compared to a typical static setting of the back-propagation ratio.
The efficient support of Hardwae-In-theLoop (HIL) in the design process of hardwaresoftware-co-designed systems is an ongoing challenge. This paper presents a network-based integration of hardware elements into the softwarebased image processing tool „ADTF“, based on a high-performance Gigabit Ethernet MAC and a highly-efficient TCP/IP-stack. The MAC has been designed in VHDL. It was verified in a SystemCsimulation environment and tested on several Altera FPGAs.
The paper describes the methodology and experimental results for revealing similarities in thermal dependencies of biases of accelerometers and gyroscopes from 250 inertial MEMS chips (MPU-9250). Temperature profiles were measured on an experimental setup with a Peltier element for temperature control. Classification of temperature curves was carried out with machine learning approach.
A perfect sensor should not have thermal dependency at all. Thus, only sensors inside the clusters with smaller dependency (smaller total temperature slopes) might be pre-selected for production of high accuracy inertial navigation modules. It was found that no unified thermal profile (“family” curve) exists for all sensors in a production batch. However, obviously, sensors might be grouped according to their parameters. Therefore, the temperature compensation profiles might be regressed for each group. 12 slope coefficients on 5 degrees temperature intervals from 0°C to +60°C were used as the features for the k-means++ clustering algorithm.
The minimum number of clusters for all sensors to be well separated from each other by bias thermal profiles in our case is 6. It was found by applying the elbow method. For each cluster a regression curve can be obtained.
Environmental Monitoring is an attractive application field for Wireless Sensor Network (WSN). Water Level Monitoring helps to increase the efficiency of water distribution and management. In Pakistan, the world’s largest irrigation system covers 90.000 km of channels which needs to be monitored and managed on different levels. Especially the sensor systems for the small distribution channels need to be low energy and low cost. The distribution presents a technical solution for a communication system which is developed in a research project being co-funded by German Academic Exchange Service (DAAD). The communication module is based on IEEE-802.15.4 transceivers which are enhanced through Wake-On-Radio (WOR) to combine low-energy and real-time behavior. On higher layers, IPv6 (6LoWPAN) and corresponding routing protocols like Routing Protocol for Low power and Lossy Networks (RPL) can extend range of the network. The data are stored in a database and can be viewed online via a web interface. Of course, also automatic data analysis can be performed.
The Metering Bus, also known as M-Bus, is a European standard EN13757-3 for reading out metering devices, like electricity, water, gas, or heat meters. Although real-life M-Bus networks can reach a significant size and complexity, only very simple protocol analyzers are available to observe and maintain such networks. In order to provide developers and installers with the ability to analyze the real bus signals easily, a web-based monitoring tool for the M-Bus has been designed and implemented. Combined with a physical bus interface it allows for measuring and recording the bus signals. For this at first a circuit has been developed, which transforms the voltage and current-modulated M-Bus signals to a voltage signal that can be read by a standard ADC and processed by an MCU. The bus signals and packets are displayed using a web server, which analyzes and classifies the frame fragments. As an additional feature an oscilloscope functionality is included in order to visualize the physical signal on the bus. This paper describes the development of the read-out circuit for the Wired M-Bus and the data recovery.
Machine-to-machine communication is continuously extending to new application fields. Especially smart metering has the potential to become the first really large-scale M2M application. Although in the future distributed meter devices will be mainly connected via dedicated primary communication protocols, like ZigBee, Wireless
M-Bus or alike, a major percentage of all meters will be connected via point to point communication using GPRS or UMTS platforms. Thus, such meter devices have to be extremely cost and energy efficient, especially if the devices are battery based and powered several years by a single battery. This paper presents the development of an automated measurement unit for power and time, thus energy characteristics can be recorded. The measurement unit includes a hardware platform for the device
under test (DUT) and a database based software environment for a smooth execution and analysis of the measurements.
Die zunehmende Anzahl von Transistoren mit immer kleineren Strukturgrößen führt zu einer zunehmenden Leistungsaufnahme in modernen Prozessoren. Das gilt insbesondere für High-End Prozessoren, die mit einer hohen Taktfrequenz betrieben werden. Die aufgenommene Leistung wird in Wärme umgewandelt, die in einer Temperaturerhöhung der Prozessoren resultiert. Hohe Betriebstemperaturen verursachen u.a. eine verringerte Rechenleistung, eine kürzere Lebensdauer des Prozessors und höhere Leckströme. Aus diesen Gründen wird aktives, dynamisches thermisches Management immer wichtiger. Dieser Beitrag stellt eine Erweiterung zu dem Standard- Linux-Scheduler in der Kernel-Version 3.0 für eingebettete Systeme vor: einen PID-Regler, der unter Angabe einer Solltemperatur eine dynamische Frequenz- und Spannungsskalierung durchführt. Die Experimente auf dem Freescale LMX6 Quadcore-Prozessor zeigen, dass der PID-Regler die Betriebstemperatur des Prozessors an die Solltemperatur regeln kann. Er ist die Grundlage für eine in Zukunft zu entwickelnde prädiktive Regelung.
Android is an operating system which was developed for use in smart mobile phones and is the current leader in this market. A lot of efforts are being spent to make Android available to the embedded world, as well. Many embedded systems do not have a local GUI and are therefore called headless devices. This paper presents the results of an analysis of the general suitability of Anroid in headless embedded systems and ponders the advantages and disadvantages. It focuses on the hardware related issues, i.e. to what extent Android supports hardware peripherals normally used in embedded systems.
The importance of machine learning has been increasing dramatically for years. From assistance systems to production optimisation to support the health sector, almost every area of daily life and industry comes into contact with machine learning. Besides all the benefits that ML brings, the lack of transparency and the difficulty in creating traceability pose major risks. While there are solutions that make the training of machine learning models more transparent, traceability is still a major challenge. Ensuring the identity of a model is another challenge. Unnoticed modification of a model is also a danger when using ML. One solution is to create an ML birth certificate and an ML family tree secured by blockchain technology. Important information about training and changes to the model through retraining can be stored in a blockchain and accessed by any user to create more security and traceability about an ML model.
Spatially Distributed Wireless Networks (SDWN) are one of the basic technologies for the Internet of Things (IoT) and (Industrial) Internet of Things (IIoT) applications. These SDWN for many of these applications has strict requirements such as low cost, simple installation and operations, and high potential flexibility and mobility. Among the different Narrowband Wireless Wide Area Networking (NBWWAN) technologies, which are introduced to address these categories of wireless networking requirements, Narrowband Internet of Things (NB-IoT) is getting more traction due to attractive system parameters, energy-saving mode of operation with low data rates and bandwidth, and its applicability in 5G use cases. Since several technologies are available and because the underlying use cases come with various requirements, it is essential to perform a systematic comparative analysis of competing technologies to choose the right technology. It is also important to perform testing during different phases of the system development life cycle. This paper describes the systematic test environment for automated testing of radio communication and systematic measurements of the performance of NB-IoT.
In this paper, we study the runtime performance of symmetric cryptographic algorithms on an embedded ARM Cortex-M4 platform. Symmetric cryptographic algorithms can serve to protect the integrity and optionally, if supported by the algorithm, the confidentiality of data. A broad range of well-established algorithms exists, where the different algorithms typically have different properties and come with different computational complexity. On deeply embedded systems, the overhead imposed by cryptographic operations may be significant. We execute the algorithms AES-GCM, ChaCha20-Poly1305, HMAC-SHA256, KMAC, and SipHash on an STM32 embedded microcontroller and benchmark the execution times of the algorithms as a function of the input lengths.