Titlebook: Malware Analysis Using Artificial Intelligence and Deep Learning; Mark Stamp,Mamoun Alazab,Andrii Shalaginov Book 2021 The Editor(s) (if a

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and tectosilicates. Due to the huge amount of data these chapters had to be spread over several subvolumes I1, I2, etc. . - In each chapter the different groups of minerals and synthetic silicates were distinctly analyzed in various sections. For each group, additional silicate minerals, more recen

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Malware Detection with Sequence-Based Machine Learning and Deep Learningnput formats, such as one-hot encoding and vector embeddings, the architecture of the machine learning models, the training process, and the output formats. Finally, we discuss commercial and open-source tools that are used for data extraction from software.

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Book 2021sis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain know