Cyber security is increasingly recognized as an essential topic for automotive systems, especially in the area of connected and automated driving. Upcoming regulation defines requirements for cyber security on multiple levels in the automotive domain in order to achieve type approval. On the organizational level, a cyber security management system (CSMS) which covers the whole vehicle lifecycle and ecosystem is required. In addition, an argumentation for the cyber security of each vehicle type for which type approval is requested has to be given. Due to the novel nature of these requirements compared to existing type approval requirements, a test phase is ongoing. The components and scope of a CSMS are an open issue. We give an overview of the requirements for a CSMS, identify approaches and gaps, and give an outlook towards a potential framework which can address the requirements.

Synchronized and precisely timestamped data from perception sensors is highly advantageous for the low-level fusion of multiple sensor data. Many open-available, low-cost perception sensors do neither provide hardware support for precise clock synchronization, nor provide timestamps with their measurement data. In this work, we present an approach to enable synchronization and accurate timestamping of hardware-triggerable sensors in multi-sensor perception systems.We utilize a hybrid timestamping approach, taking into account the timestamp of a hardware trigger and the software timestamp. The presented timestamping approach utilizes the trigger time to assign precise timestamps to the data streams of the perception sensors. Precise timestamps are mandatory in order to achieve a high perception performance in dynamic applications which utilize low-level data streams.Additionally, we present an implementation of the approach on a multi-sensor perception platform, archiving a timestamp precision in the range of 2 ms. An existing Robot Operating System (ROS) architecture of the platform is extended to assign hybrid timestamps to the data streams. Additionally, we present a pedestrian detection implementation which fuses the timestamped data into a representation.

We present an approach to fuse radar and time-of-flight (ToF) range sensor data into an occupancy grid. Fusing the low-level data at sensor level prevents the loss of precious information during compression and pre-processing. Constructing the low-level occupancy grid from raw sensor data enables the detection of occupied cells which are not clearly visible by any of the single sensors. Fusion of the heterogeneous sensor data enhances the perception quality since single sensors fail in certain conditions. Thus, the fusion at low-level holds a high potential to enhance the perception quality for automotive/robotic applications. We demonstrate our approach with real-world data from a mobile sensor platform with three ToF cameras and a 77 GHz high-resolution radar sensor. An occupancy grid is created whenever synchronized sensor data from all sensors is available. The proposed method performed successful detection of multiple pedestrians in different test scenarios. Our approach to build an occupancy grid from radar and optical range sensors can be used as a base in various short-range perception applications (e.g., in robotics or mobile devices).

Smart maintenance constitutes an essential concept in Industry 4.0, where industrial devices report their maintenance status to remote back end systems and thus predictive maintenance can be intelligently scheduled and carried out locally at the affected device. This status data must be securely assignable to the claimed device identities when transmitted remotely. Furthermore, during the actual maintenance task, the service technician must be able to trustworthily identify the correct target device. Unfortunately, current systems typically lack cryptographic authentication and a secure storage for the required credentials, causing identity impersonation as a major threat. In this paper we present a secure NFC-enabled hardware module for industrial embedded systems with a secure identity, enabling local identification by means of the proximity based contact-less technology Near Field Communication (NFC), and remote identification via a contact-based interface, thus helping to prevent device impersonation attacks, device clones and human errors on device identification. A proof of concept utilizing an Infineon security controller capable of elliptic curve cryptography demonstrates the concepts feasibility.

The certification process of COTS (commercial off-the-shelf) components is getting more important as we move towards the software component marketplace. We identify specifications used for certification tests and associations between them. Specifications are defined using UML (Unified Modeling Language) notations and are shown in the example of the ASAM-GDI (Automation and Measuring Systems Generic Device Interface) standard, which defines standard interfaces to devices and device drivers in automation and measurement systems. It is shown that UML is suitable for this purpose. Furthermore, it offers a platform-independent notation, which can be mapped to a specific language and technology, i.e. to an execution model that is appropriate for integration in a client system. We propose that reusability of COTS components should include not only the COTS component, but also specifications defining test cases. This way, it is possible for the client to quickly verify COTS components and to avoid the component misuse problem.

The scalable coherent interface (SCI) defines a high-speed interconnect system that provides a coherent memory system. It specifies a topology-independent communication protocol with the possibility of connecting up to 64 K nodes. SCI switches are the key components in building large SCI systems effectively. An SCI switch which uses several internal buses is studied as well as more complex systems composed of several switches. Computer simulations are used to compare the different models and to determine system parameters.