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Machine Learning for Embedded System Security 2022 edition
Machine Learning for Embedded System Security
This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.
160 pages, 75 Tables, color; 39 Illustrations, color; 27 Illustrations, black and white; XV, 160 p.
| Medios de comunicación | Libros Hardcover Book (Libro con lomo y cubierta duros) |
| Publicado | 23 de abril de 2022 |
| ISBN13 | 9783030941772 |
| Editores | Springer Nature Switzerland AG |
| Páginas | 160 |
| Dimensiones | 165 × 242 × 17 mm · 426 g |
| Lengua | Alemán |
| Editor | Halak, Basel |