Related papers: Enhancing Attack Resilience in Real-Time Systems t…
Adaptive scheduling is crucial for ensuring the reliability and safety of time-triggered systems (TTS) in dynamic operational environments. Scheduling frameworks face significant challenges, including message collisions, locked loops from…
Efficient runtime task scheduling on complex memory hierarchy becomes increasingly important as modern and future High-Performance Computing (HPC) systems are progressively composed of multisocket and multi-chiplet nodes with nonuniform…
Complex, interconnected cyber-physical systems (CPS) are increasingly prevalent in domains such as power systems. Cyber-resilient architectures have been proposed to recover compromised cyber components of CPS. Recent works have studied…
Cyber-Physical Systems play a critical role in the infrastructure of various sectors, including manufacturing, energy distribution, and autonomous transportation systems. However, their increasing connectivity renders them highly vulnerable…
This work addresses the problem of exact schedulability assessment in uniprocessor mixed-criticality real-time systems with sporadic task sets. We model the problem by means of a finite automaton that has to be explored in order to check…
Caches have been exploited to leak secret information due to the different times they take to handle memory accesses. Cache timing attacks include non-speculative cache side and covert channel attacks and cache-based speculative execution…
This article proposes a Model Reference Adaptive Control (MRAC) strategy to achieve fixed-time convergence of parameter estimation and tracking errors for unknown linear time-invariant systems, without relying on the persistence of…
This paper introduces a novel reinforcement learning (RL) approach to scheduling mixed-criticality (MC) systems on processors with varying speeds. Building upon the foundation laid by [1], we extend their work to address the non-preemptive…
Detecting kinetic vulnerabilities in Cyber-Physical Systems (CPS), vulnerabilities in control code that can precipitate hazardous physical consequences, is a critical challenge. This task is complicated by the need to analyze the intricate…
Security metrics serve as a powerful tool for organizations to understand the effectiveness of protecting computer networks. However majority of these measurement techniques don't adequately help corporations to make informed risk…
Industrial process control systems are time-critical systems where reliable communications between sensors and actuators need to be guaranteed within strict deadlines to maintain safe operation of all the components of the system.…
This work studies the threats of adversarial attack on multivariate probabilistic forecasting models and viable defense mechanisms. Our studies discover a new attack pattern that negatively impact the forecasting of a target time series via…
Mixed-criticality real-time scheduling has been developed to improve resource utilization while guaranteeing safe execution of critical applications. These studies use optimistic resource reservation for all the applications to improve…
This paper considers an opportunistic scheduling problem over a renewal system. A controller observes a random event at the beginning of each renewal frame and then chooses an action in response to the event, which affects the duration of…
Critical infrastructure increasingly relies on interconnected cyber-physical systems whose security incidents can escalate rapidly into safety and operational failures. Existing decision-support approaches struggle to support real-time…
Persistent monitoring of dynamic targets is essential in real-world applications such as disaster response, environmental sensing, and wildlife conservation, where mobile agents must continuously gather information under uncertainty. We…
High-performance computing (HPC) systems consume enormous amounts of energy, with idle nodes as a major source of energy waste. Powering down idle nodes can mitigate this problem, but long boot/shutdown delays can introduce significant…
Cyber-physical systems (CPS) offer immense optimization potential for manufacturing processes through the availability of multivariate time series data of actors and sensors. Based on automated analysis software, the deployment of adaptive…
Data-driven techniques are used in cyber-physical systems (CPS) for controlling autonomous vehicles, handling demand responses for energy management, and modeling human physiology for medical devices. These data-driven techniques extract…
Parametric analysis is a powerful tool for designing modern embedded systems, because it permits to explore the space of design parameters, and to check the robustness of the system with respect to variations of some uncontrollable…