| 書目名稱 | Malware Analysis Using Artificial Intelligence and Deep Learning |
| 編輯 | Mark Stamp,Mamoun Alazab,Andrii Shalaginov |
| 視頻video | http://file.papertrans.cn/623/622007/622007.mp4 |
| 概述 | Explores how deep learning and artificial intelligence can effectively be used in malware detection and analysis.Showcases state-of-the-art tools, frameworks and techniques to enable readers to implem |
| 圖書封面 |  |
| 描述 | .?This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. 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 knowledge of malware is needed..This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.. |
| 出版日期 | Book 2021 |
| 關(guān)鍵詞 | Malware identification and analysis; Intrusion detection; Computer forensics; Spam detection; Phishing d |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-62582-5 |
| isbn_softcover | 978-3-030-62584-9 |
| isbn_ebook | 978-3-030-62582-5 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機(jī)版|小黑屋|
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