Kniha Malware Dimitris Gritzalis

Malware

Handbook of Prevention and Detection

Jazyk: Angličtina
Vazba: Pevná
Vydavatel: Springer, Berlin
Dostupnost: Skladem u dodavatele
Odesíláme za 10-13 dnů
5 251
This book provides a holistic overview of current state of the art and practice in malware research...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Pevná
Vydáno
2024
Stránek
434
EAN
9783031662447
Enbook ID
46145432
Vydavatel
Hmotnost
775
Rozměry
155 x 235

Kompletní popis

This book provides a holistic overview of current state of the art and practice in malware research as well as the challenges of malware research from multiple angles. It also provides step-by-step guides in various practical problems, such as unpacking real-world malware and dissecting it to collect and perform a forensic analysis. Similarly, it includes a guide on how to apply state-of-the-art Machine Learning methods to classify malware. Acknowledging that the latter is a serious trend in malware, one part of the book is devoted to providing the reader with the state-of-the-art in Machine Learning methods in malware classification, highlighting the different approaches that are used for, e.g., mobile malware samples and introducing the reader to the challenges that are faced when shifting from a lab to production environment.

Modern malware is fueling a worldwide underground economy. The research for this book is backed by theoretical models that simulate how malware propagates and how the spread could be mitigated. The necessary mathematical foundations and probabilistic theoretical models are introduced, and practical results are demonstrated to showcase the efficacy of such models in detecting and countering malware. It presents an outline of the methods that malware authors use to evade detection. This book also provides a thorough overview of the ecosystem, its dynamics and the geopolitical implications are introduced. The latter are complemented by a legal perspective from the African legislative efforts, to allow the reader to understand the human and social impact of malware.

This book is designed mainly for researchers and advanced-level computer science students trying to understand the current landscape in malware, as well as applying artificial intelligence and machine learning in malware detection and classification. Professionals who are searching for a perspective to streamline the challenges that arise, when bringing lab solutions into a production environment, and how to timely identify ransomware signals at scale will also want to purchase this book. Beyond data protection experts, who would like to understand how malware siphons private information, experts from law enforcement authorities and the judiciary system, who want to keep up with the recent developments will find this book valuable as well.

 

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