Da: Bellwetherbooks, McKeesport, PA, U.S.A.
EUR 28,62
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrellopaperback. Condizione: Very Good. Very Good Condition - May show some limited signs of wear and may have a remainder mark. Pages and dust cover are intact and not marred by notes or highlighting.
Da: ChristianBookbag / Beans Books, Inc., Westlake, OH, U.S.A.
EUR 38,26
Convertire valutaQuantità: 5 disponibili
Aggiungi al carrellopaperback. Condizione: New. New with remainder mark. Buy multiples from our store to save on shipping.
Da: Massive Bookshop, Greenfield, MA, U.S.A.
EUR 44,28
Convertire valutaQuantità: 10 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 11/7/2023.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 39,31
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 526.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 44,06
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloCondizione: New. In.
Editore: No Starch Press 2023-11-07, 2023
ISBN 10: 171850330X ISBN 13: 9781718503304
Lingua: Inglese
Da: Chiron Media, Wallingford, Regno Unito
EUR 41,98
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: New.
Editore: Random House LLC US Nov 2023, 2023
ISBN 10: 171850330X ISBN 13: 9781718503304
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 47,06
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: 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: