The rapid expansion of Cyber-Physical Systems (CPS), their extensiveness, and their wide range of applications have introduced several new security challenges, particularly in critical infrastructures such as smart grids or vehicles. The growing attack techniques, diversity of devices, and network technologies are becoming more sophisticated, making the infrastructure more vulnerable. Meanwhile, machine learning-based intrusion detection systems (IDS) for CPS have struggled to keep up due to the lack of datasets and limited variability in attack types and system architectures. Therefore, it is essential to improve the diversity, quality, and representativeness of datasets used to train CPS IDSs. This work aims to present a framework capable of automatically execute attack chains in simulated CPS environments, producing datasets to aid the development of effective IDSs. The framework leverages an ontology that allows the tool to interpret attack paths and be easily extensible.
Ada has held its own in the safety critical space for just over 4 decades. Over the last 10 years Rust has pushed into the same space with varying success. Among other features, most notably Rust is missing the powerful declarations and convenience of use of subtypes. In this talk at the FOSDEM 2025 Ada Developer Room I went into the various features that make Ada so useful for ensuring the absence of bugs, and where Rust stands on each of these features.
Performance requirements in critical real-time embedded systems continue to grow steadily, while energy management constraints are becoming increasingly significant. To meet this challenge, only multi-core processors can provide a viable solution. However, using such processors presents major difficulties in systems that require guaranteed real-time behaviour. Due to interferences caused by the access to shared resources, performance optimization of processing tasks, and the lack of detailed documentation about the internal workings of multi-core processors, the real-time behaviour of applications running on these multi-cores can no longer be assured. With the Open Hardware Group initiative and the rise of RISC-V, new open-source processors are emerging, creating the opportunity to adapt a core (such as CVA6) with the appropriate properties for critical embedded systems. This is the research hypothesis pursued for the past four years by the TRACES team at IRIT, which has modified the CVA6 core to make it temporally predictable and thus formally guarantee the required real-time properties. The initial results led to the submission and acceptance of the ANR-ASTRID PRINTEmPS project (PRedictable and Safe INTErconnect and PRocessor), whose objective is to develop a predictable multi-core processor (demonstrator) and an analysis platform for worst-case execution and response times, compatible with this processor. The project started in January 2023. During the first year of the project, we have started by identifying a representative case-study: quadcopter stabilization software. This software is responsible for maintaining the balance and orientation of the drone during flight by continuously adjusting motor speeds based on sensor feedback (e.g., gyroscopes, accelerometers). It implements control algorithms, such as PID controllers, that process real-time data to issue precise commands to each of the four motors. Using four separate threads—one per motor—on a quad-core processor allows for parallel execution of motor control tasks, closely mimicking the real-time requirements of an actual drone. This setup is ideal for evaluating the real-time performance and determinism of a quad-core processor, as it tests the processor's ability to handle synchronized, latency-sensitive workloads with interferences. This case study will also verify the hardware design of the multi-core processor and its analysis platform (WCET and WCRT).
FOSDEM is a huge open source event organized each year in Brussels, Belgium. Among others, it features dozens of tracks on specific topics: the s.c. Developer Rooms. This year, for the 12 th time, there was a track about the Ada programming language and related technologies. A brief overview of the half-day "Ada DevRoom" program is given, followed by reports of all technical presentations by their respective authors.
Energy Monitoring Systems (EMS) are IoT systems that track measurements regarding energy production and consumption within houses, communities, or even industrial buildings. Designing these systems is still complex and requires careful consideration of heterogeneous devices, their hardware and software components, and especially their limitations. This work presents a model-driven development methodology for EMS, mainly focused on the house level. The approach allows the modeling of these systems and to perform a viability analysis of a designed system. The viability analysis is especially focused on validation scheduling configurations for the measurements, or to automatically provide viable scheduling configurations when needed.
