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Malware Handbook of Prevention and Detection /

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 collec...

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Ente Autore: SpringerLink (Online service)
Altri autori: Gritzalis, Dimitris (Redattore), Choo, Kim-Kwang Raymond (Redattore), Patsakis, Constantinos (Redattore)
Natura: Elettronico eBook
Lingua:inglese
Pubblicazione: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edizione:1st ed. 2025.
Serie:Advances in Information Security, 91
Soggetti:
Data protection > Law and legislation.
Artificial intelligence.
Computer networks > Security measures.
Privacy.
Artificial Intelligence.
Mobile and Network Security.
Accesso online:https://doi.org/10.1007/978-3-031-66245-4
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Sommario:
  • Part I Theoretical foundation and modeling
  • Chapter 1 Classifying Malware using Tensor Decomposition
  • Chapter 2 Radial Spike and Slab Bayesian Neural Networks for Sparse Data in Ransomware Attacks
  • Chapter 3 Mathematical models for malware propagation: state of art and perspectives
  • Chapter 4 Botnet Defense System: A System to Fight Botnets with Botnets
  • Part II Machine learning for malware classification
  • Chapter 5 Machine Learning-Based Malware Detection in a Production Setting
  • Chapter 6 Machine Learning for Windows Malware Detection and Classification: Methods, Challenges and Ongoing Research
  • Chapter 7 Conventional Machine Learning-based Android Malware Detectors
  • Chapter 8 Conventional Machine Learning-based Android Malware Detectors
  • Chapter 9 Method to automate the classification of PE32 malware using Word2vec and LSTM
  • Part III Social and legal
  • Chapter 10 The South African and Senegalese legislative response to malware facilitated cybercrime
  • Chapter 11Malware as a Geopolitical Tool.-Part IV Malware analysis in practice and evasions
  • Chapter 12 Advancements in Malware Evasion: Analysis Detection and the Future Role of AI.-Chapter 13 Unpacking malware in the real world: a step by step guide
  • Chapter 14 Forensic Analysis of CapraRAT Android Malware
  • Chapter 15 Hidden Realms: Exploring Steganography Methods in Games for Covert Malware Delivery
  • Part V Malware ecosystem
  • Chapter 16 The Malware as a Service ecosystem
  • Chapter 17Preventing and detecting malware in smart environments. The smart home case.

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