Isomorphism between Linear Codes and Arithmetic Codes for Safe Data Processing in Embedded Software Systems

We present a transformation rule to convert linear codes into arithmetic codes. Linear codes are usually used for error detection and correction in broadcast and storage systems. In contrast, arithmetic codes are very suitable for protection of software processing in computer systems. This paper shows how to transform linear codes protecting the data stored in a computer system into arithmetic codes safeguarding the operations built on this data. Combination of the advantages of both coding mechanisms will increase the error detection capability in safety critical applications for embedded systems by detection and correction of arbitrary hardware faults

Causality and Functional Safety - How Causal Models Relate to the Automotive Standards ISO 26262, ISO/PAS 21448, and UL 4600

With autonomous driving, the system complexity of vehicles will increase drastically. This requires new ap- proaches to ensure system safety. Looking at standards like ISO 26262 or ISO/PAS 21448 and their suggested methodologies, an increasing trend in the recent literature can be noticed to incorporate uncertainty. Often this is done by using Bayesian Networks as a framework to enable probabilistic reasoning. These models can also be used to represent causal relationships. Many publications claim to model cause-effect relations, yet rarely give a formal introduction of the implications and resulting possibilities such an approach may have. This paper aims to link the domains of causal reasoning and automotive system safety by investigating relations between causal models and approaches like FMEA, FTA, or GSN. First, the famous “Ladder of Causation” and its implications on causality are reviewed. Next, we give an informal overview of common hazard and reliability analysis techniques and associate them with probabilistic models. Finally, we analyse a mixed-model methodology called Hybrid Causal Logic, extend its idea, and build the concept of a causal shell model of automotive system safety

Security-Gateway for SCADA-Systems in Critical Infrastructures

The presented work is part of the research project Energy Safe and Secure System Module (ES3M), which is funded by the Project Management J ̈ulich (PtJ) and the German Federal Ministry for Economic Affairs and Energy (BMWi) under funding code 0350042ASupervisory Control and Data Acquisition (SCADA) systems are used to control and monitor components within the energy grid, playing a significant role in the stability of the system. As a part of critical infrastructures, components in these systems have to fulfill a variety of different requirements regarding their dependability and must also undergo strict audit procedures in order to comply with all relevant standards. This results in a slow adoption of new functionalities. Due to the emerged threat of cyberattacks against critical infrastructures, extensive security measures are needed within these systems to protect them from adversaries and ensure a stable operation. In this work, a solution is proposed to integrate extensive security measures into current systems. By deploying additional security-gateways into the communication path between two nodes, security features can be integrated transparently for the existing components. The developed security-gateway is compliant to all regulatory requirements and features an internal architecture based on the separation-of-concerns principle to increase its security and longevity. The viability of the proposed solution has been verified in different scenarios, consisting of realistic field tests, security penetration tests and various performance evaluations

CausalOps -- Towards an Industrial Lifecycle for Causal Probabilistic Graphical Models

Causal probabilistic graph-based models have gained widespread utility, enabling the modeling of cause-and-effect relationships across diverse domains. With their rising adoption in new areas, such as automotive system safety and machine learning, the need for an integrated lifecycle framework akin to DevOps and MLOps has emerged. Currently, a process reference for organizations interested in employing causal engineering is missing. To address this gap and foster widespread industrial adoption, we propose CausalOps, a novel lifecycle framework for causal model development and application. By defining key entities, dependencies, and intermediate artifacts generated during causal engineering, we establish a consistent vocabulary and workflow model. This work contextualizes causal model usage across different stages and stakeholders, outlining a holistic view of creating and maintaining them. CausalOps' aim is to drive the adoption of causal methods in practical applications within interested organizations and the causality community

An optimized Bitsliced Masked Adder for ARM Thumb-2 Controllers

The modular addition is used as a non-linear operation in ARX ciphers because it achieves the requirement of introducing non-linearity in a cryptographic primitive while only taking one clock cycle to execute on most modern archi- tectures. This makes ARX ciphers especially fast in software implementations, but comes at the cost of making it harder to protect against side-channel information leakages using Boolean masking: the best known 2-shares masked adder for ARM Thumb micro-controllers takes 83 instructions to add two 32-bit numbers together. Our approach is to operate in bitsliced mode, performing 32 additions in parallel on a 32-bit microcontroller. We show that, even after taking into account the cost of bitslicing before and after the encryption, it is possible to achieve a higher throughput on the tested ciphers (CRAX and ChaCha20) when operating in bitsliced mode. Furthermore, we prove that no first-order information leakage is happening in either simulated power traces and power traces acquired from real hardware, after sufficient countermeasures are put into place to guard against pipeline leakages

Using Augmented Reality in Software Engineering Education? First insights to a comparative study of 2D and AR UML modeling

Although there has been much speculation about the potential of Augmented Reality (AR) in teaching for learning material, there is a significant lack of empirical proof about its effectiveness and implementation in higher education. We describe a software to integrate AR using the Microsoft Hololens into UML (Unified Modeling Language) teaching. Its user interface is laid out to overcome problems of existing software. We discuss the design of the tool and report a first evaluation study. The study is based upon effectiveness as a metric for students performance and components of motivation. The study was designed as control group experiment with two groups. The experimental group had to solve tasks with the help of the AR modeling tool and the control group used a classic PC software. We identified tendencies that participants of the experimental group showed more motivation than the control group. Both groups performed equally well

Entwicklung eines Manifests für spielifizierte Hochschullehre

In dieser Veröffentlichung präsentieren die Autoren erste Ergebnisse Ihrer Forschungsarbeit an einem Manifest für spielifizierte Hochschullehre. Ausgehend von einer Literaturrecherche über den aktuellen Forschungsstand werden erste Auszüge der aktuellen Arbeit dargestellt, auf deren Basis ein aktiver wissenschaftlicher Diskurs angeregt werden soll

Causality and Functional Safety - How Causal Models Relate to the Automotive Standards ISO 26262, ISO/PAS 21448, and UL 4600

With autonomous driving, the system complexity of vehicles will increase drastically. This requires new ap- proaches to ensure system safety. Looking at standards like ISO 26262 or ISO/PAS 21448 and their suggested methodologies, an increasing trend in the recent literature can be noticed to incorporate uncertainty. Often this is done by using Bayesian Networks as a framework to enable probabilistic reasoning. These models can also be used to represent causal relationships. Many publications claim to model cause-effect relations, yet rarely give a formal introduction of the implications and resulting possibilities such an approach may have. This paper aims to link the domains of causal reasoning and automotive system safety by investigating relations between causal models and approaches like FMEA, FTA, or GSN. First, the famous “Ladder of Causation” and its implications on causality are reviewed. Next, we give an informal overview of common hazard and reliability analysis techniques and associate them with probabilistic models. Finally, we analyse a mixed-model methodology called Hybrid Causal Logic, extend its idea, and build the concept of a causal shell model of automotive system safety

Security-Gateway for SCADA-Systems in Critical Infrastructures

The presented work is part of the research project Energy Safe and Secure System Module (ES3M), which is funded by the Project Management J ̈ulich (PtJ) and the German Federal Ministry for Economic Affairs and Energy (BMWi) under funding code 0350042ASupervisory Control and Data Acquisition (SCADA) systems are used to control and monitor components within the energy grid, playing a significant role in the stability of the system. As a part of critical infrastructures, components in these systems have to fulfill a variety of different requirements regarding their dependability and must also undergo strict audit procedures in order to comply with all relevant standards. This results in a slow adoption of new functionalities. Due to the emerged threat of cyberattacks against critical infrastructures, extensive security measures are needed within these systems to protect them from adversaries and ensure a stable operation. In this work, a solution is proposed to integrate extensive security measures into current systems. By deploying additional security-gateways into the communication path between two nodes, security features can be integrated transparently for the existing components. The developed security-gateway is compliant to all regulatory requirements and features an internal architecture based on the separation-of-concerns principle to increase its security and longevity. The viability of the proposed solution has been verified in different scenarios, consisting of realistic field tests, security penetration tests and various performance evaluations