Titlebook: Data Science and Applications; Proceedings of ICDSA Satyasai Jagannath Nanda,Rajendra Prasad Yadav,Muk Conference proceedings 2024 The Edit

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Peter Fissenewert,Mathias Wendton of brain tumors into three main categories: benign, malignant, and pituitary. A comprehensive analysis of the major research papers in this field is presented, covering the different deep learning architectures and techniques used, and their performance in detecting and classifying brain tumors w

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Bank- und Kapitalmarkt-Compliancemanufacturing stages. It has the potential to manipulate circuit performance or acquire underlying information. Due to machine learning’s (ML) exceptional results across a range of learning domains, the academic and business community are now looking at how Hardware Trojan (HT) attacks can be streng

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Thomas Schwartz,Nikolaus Seitz Dipl.-Kfm.ine learning methods for identifying malware frequently encounter privacy dilemmas and scalability challenges. In this study, we introduce a method based on federated learning to detect IoT malware. This method promotes cooperative learning across dispersed IoT devices, ensuring data confidentiality

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https://doi.org/10.1007/978-3-658-01270-0o the lack of authentication and the trust-based nature of the protocol. As a result, BGP attacks are becoming increasingly common, causing significant damage to network availability and security. In this paper, we propose a deep learning-based approach to improve BGP security. Our approach uses a n

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https://doi.org/10.1007/978-981-99-7862-5Models and Algorithms; Data Science Applications; Data Science Challenges; Machine Learning; Data Mining

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978-981-99-7861-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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