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Browsing Staff publications (MMD) by Publisher "IEEE"

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    From raw data to monotonic and trendable features reflecting degradation trends in turbofan engines
    (IEEE, 2024-12-08) Fuad, Mohd Fazril Irfan Ahmad; Khan, Samir; Erkoyuncu, John Ahmet
    The performance of prognostic models relies heavily on the form and trend of the extracted features. However, the raw data collected from physical systems are inherently noisy, large in volume, and exhibit significant variability, which makes them unsuitable for direct use in prognostics. These characteristics poorly reflect the degradation behavior of physical systems and contribute to the uncertainty of prognostic outcome. Hence, transforming this data into relevant features and carefully selecting them is crucial for meeting the specific needs of prognostic models. This paper aims to address data processing challenges by focusing on extraction and selection of high-quality monotonic features which clearly reflect the degradation and can reduce prognostics uncertainty. The proposed framework comprises three main stages: Data pre-processing, feature extraction, and feature selection. It includes a fitness analysis to evaluate the monotonicity and trendability of features supplemented by visual inspections to identify relevant features. Applied to the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) dataset from the NASA Ames Prognostics Data Repository, the framework reduces noise, improves feature monotonicity and trendability, and facilitates the selection of useful features - essential aspects for effective prognostic methods.
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    ROSE+ : A robustness-optimized security scheme against cascading failures in multipath TCP under LDDoS attack streams
    (IEEE, 2024-12-17) Nie, Jinquan; Ji, Lejun; Jiang, Yirui; Ma, Young; Cao, Yuanlong
    Multipath TCP leverages parallel data transmission across multiple paths to improve transmission rates, reliability, and resource utilization. However, Multipath TCP faces severe network security and communication reliability challenges when exposed to low-rate distributed denial-of-service (LDDoS) attacks. In this paper, we propose a robustness optimization security scheme against cascading failures in Multipath TCP (ROSE+) to tackle the challenges posed by Low-rate Distributed Denial of Service (LDDoS) attacks on network security and communication reliability. The scheme integrates the intricate network load-capacity cascading failures model and leverages the unique characteristics of multipath TCP to facilitate the redistribution of load traffic at ineffectiveness nodes, thereby alleviating the cascading failures induced by LDDoS attack streams. Additionally, we optimize the robustness of communication transmission systems by devising a load-capacity cascading failures model. The experimental results demonstrate that the scheme reduces the probability of cascading failures by 20.07%. This research provides new ideas and methods to improve the robustness and destruction resistance of multipath TCP transmission.