Titlebook: Algorithms and Architectures for Parallel Processing; 23rd International C Zahir Tari,Keqiu Li,Hongyi Wu Conference proceedings 2024 The Ed

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https://doi.org/10.1007/978-3-642-51379-4erage and global connectivity. However, due to the unique nature of satellite networks, they face the threat of DoS attacks from malicious actors. In this paper, we propose SDN-based framework and detection method for simulating and detecting DoS attacks in LEO satellite network. In terms of attack

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Abbaue auf steil einfallenden Lagerst?ttenbile devices. Malware continues to evolve and update, which often developing new variants or changing existing features to evade detection. Traditional feature based malware detection methods are limited in their ability to detect variants, and are computationally resource-intensive. Considering the

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Das Verhalten des Bodens unter Lastenicles (IoAV). If delay-sensitive vehicle tasks are not completed on time, it will lead to bad consequences for IoAV. Task offloading technology can solve the problem that the vehicle cannot meet the task requirements. However, highly dynamic vehicle networks and diverse vehicle applications require

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,Erratum to: Hohlk?rpergründungen,consumption on MDs with efficient task offloading and scheduling strategies. In this paper, we aim to minimize the weighted sum of the task processing time and energy consumption of MDs in end-edge-cloud orchestrated computing (EECOC). To solve the non-convex problem caused by joint optimization and

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,Unmittelbare Gründungen unter Wasser,atures, but struggle with flows that reveal unclear or sparse characteristics. This is a concern as malicious flows are rare and discrete in real-world situations. To overcome these challenges, this research paper introduces a novel few-shot sample malicious flow detection model that leverages data

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https://doi.org/10.1007/978-981-97-0811-6Big Data; Distributed Parallel Systems; Internet of Things; Software Systems; Programming Models; Network

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