Sprache: Englisch
Verlag: No Starch Press (edition ), 2023
ISBN 10: 171850330X ISBN 13: 9781718503304
Anbieter: BooksRun, Philadelphia, PA, USA
Paperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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In den WarenkorbPaperback. Zustand: Brand New. 280 pages. 9.25x7.00x1.02 inches. In Stock.
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Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Zustand: New. Qian Han, Research Scientist at Meta since 2021, received his PhD in Computer Science from Dartmouth College and his Bachelor&rsquos in Electronic Engineering from Tsinghua University, Beijing, China.Salvador Mandujano, Security Engin.
EUR 41,93
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Sprache: Englisch
Verlag: Random House LLC US Nov 2023, 2023
ISBN 10: 171850330X ISBN 13: 9781718503304
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system.This groundbreaking guide to Android malware distills years of research by machine learning experts in academia and members of Meta and Google's Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today.Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud.You'll:Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 298 pp. Englisch.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. The Android Malware Handbook | Detection and Analysis by Human and Machine | Qian Han (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2023 | Random House LLC US | EAN 9781718503304 | Verantwortliche Person für die EU: Springer Fachmedien Wiesbaden GmbH, Postfach:15 46, 65189 Wiesbaden, info[at]bod[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: Random House LLC US Nov 2023, 2023
ISBN 10: 171850330X ISBN 13: 9781718503304
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system.This groundbreaking guide to Android malware distills years of research by machine learning experts in academia and members of Meta and Google's Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today.Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud.You'll:
Sprache: Englisch
Verlag: Random House LLC US Nov 2023, 2023
ISBN 10: 171850330X ISBN 13: 9781718503304
Anbieter: Books-by-Floh, Paderborn, Deutschland
Taschenbuch. Zustand: Neu. Neuware -Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system.This groundbreaking guide to Android malware distills years of research by machine learning experts in academia and members of Meta and Google's Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today.Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud.You'll: 298 pp. Englisch.