https://hdl.handle.net/20.500.11984/1148 Sat, 18 Jul 2026 08:58:32 GMT 2026-07-18T08:58:32Z https://hdl.handle.net/20.500.11984/14625 Sow Smarter, Not Harder: Evaluating LLM-Generated Seeds for Fuzzing Critical Infrastructure Barredo Ferreira, Jorge; Eceiza, Maialen; Flores, Jose Luis; Iturbe Urretxa, Mikel Software vulnerabilities in critical infrastructure components can lead to severe disruptions. While fuzzing effectively identifies such weaknesses, the quality of initial seed inputs significantly impacts its effectiveness. This study evaluates how large language models (LLMs) can generate better fuzzing seeds for critical infrastructure software. We compared seven LLMs—ChatGPT-4-Turbo, Claude 3.0 Opus, Claude 3.7 Sonnet, DeepSeek-V3, Gemini 2.0 Flash, Grok 3, and Mistral 7B—with manual baselines across six programs, including industrial control libraries, routing components, and network firmware. Over 20 independent 24-h campaigns per model and program, LLM-generated seeds achieved 14.8% higher code coverage, detected 56.3% more unique crashes, and reached first crashes 373.9% faster than manual methods. Performance patterns emerged across different infrastructure protocols, with certain models excelling at complex SCADA data formats while others performed better for network security components. The 56.5% computational efficiency improvement benefits resource-constrained operational technology environments. These findings demonstrate that LLM-generated seeds can meaningfully enhance vulnerability detection in software underlying critical infrastructure systems, offering a practical approach to strengthening resilience against cyber threats . Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/20.500.11984/14625 2026-01-01T00:00:00Z https://hdl.handle.net/20.500.11984/14624 MagNet Challenge 2023 Revisited: Beyond the Bounds of Equation-Based Core Loss Modeling Arruti Romero, Asier; Agote San Sebastian, Anartz; Aizpuru, Iosu; Mazuela, Mikel This work focuses on addressing limitations and improving MU’s MagNet Challenge 2023 core loss model. MU’s core loss model is presented and explained, which formalizes and standardizes the model. Then, key limitations detected after the results of the MagNet Challenge are discussed. Some implementation issues of the model are fixed, which improves the performance of the model. In addition, upgrades to the model based on physical insight and ties with previous works are made, further improving the performance of the model. At the end, the fixed and improved model is about 60 % better accuracy and 40 % lower number of parameters. The model is designed to ease its adoption, and steps to facilitate replicating this work are taken. Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/20.500.11984/14624 2026-01-01T00:00:00Z https://hdl.handle.net/20.500.11984/14590 Active damping control strategy to avoid resonance issues in diesel-electric vessels with DC distribution systems Alacano, Argiñe; Abad, Gonzalo; Valera, Juan José This paper presents an active damping control strategy especially designed to mitigate the effects of the resonances of low damped power electronic based DC distribution systems. In those systems, some controlled converters are connected to a common DC bus usually exhibiting negative impedance due to its operation as constant power loads. The active damping control strategy is supported by a model based design approach, which defines the dynamic behavior of the entire system. It is implemented in a complete simulation model which considers the nonlinearities of the electronic power converters such as the delays or discretization, among others. The proposed control strategy improves the power quality in both, the transient and the steady state without compromising the voltage and current controllers' bandwidths. The performance of the proposed active damping control strategy is validated through several simulation results. Fri, 01 Jan 2016 00:00:00 GMT https://hdl.handle.net/20.500.11984/14590 2016-01-01T00:00:00Z https://hdl.handle.net/20.500.11984/14588 A multivariable modeling approach for the design of Power Electronics Based DC Distribution Systems in diesel-electric vessels Alacano, Argiñe; Valera, Juan José; Abad, Gonzalo The benefits of using Power Electronics Based DC Distribution Systems in diesel-electric vessels are well known. However, some aspects must be deeply analyzed to guarantee a safe, robust and stable system by design. A multivariable DC Distribution System mathematical model is presented and described in this work, where all the transmission lines and filters impedances are considered. The model has been tackled under a holistic approach in which the average small signal model of the drives/converters can be easily added and `connected' to the main grid model. The stability and signal power quality analysis, as well as the design of controls and active damping strategies can be conducted through this mathematical model at low computational cost. The usefulness of this model in the early design stages is thus presented in this paper through its application over a realistic design scenario. Fri, 01 Jan 2016 00:00:00 GMT https://hdl.handle.net/20.500.11984/14588 2016-01-01T00:00:00Z