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Cyber Threat Intelligence

Cyber Threat Intelligence


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About the Book

1 Introduction.- 2 Machine Learning Aided Static Malware Analysis.- 3 Application of Machine Learning Techniques to Detecting Anomalies in Communication Networks: Datasets and Feature Selection.- 4 Application of Machine Learning Techniques to Detecting Anomalies in Communication Networks: Classification Algorithms.- 5 Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection.- 6 Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware.- 7 BoTShark - A Deep Learning Approach for Botnet Traffic Detection.- 8 A Practical Analysis of The Rise in Mobile Phishing.- 9 PDF-Malware Detection: A Survey and Taxonomy of Current Techniques.- 10 Adaptive Traffic Fingerprinting for Darknet Threat Intelligence.- 11 A Model for Android and iOS Applications Risk Calculations: CVSS Analysis and Enhancement Using Case-Control Studies.- 12 A Honeypot Proxy Framework for Deceiving Attackers with Fabricated Content.- 13 Investigating the Possibility of Data Leakage in Time of Live VM Migration.- 14 Forensics Investigation of OpenFlow-Based SDN Platforms.- 15 Mobile Forensics: A Bibliometric Analysis.- 16 Emerging from The Cloud: A Bibliometric Analysis of Cloud Forensics Studies.


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Product Details
  • ISBN-13: 9783319739502
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Edition: 1st ed. 2018
  • Language: English
  • Returnable: Y
  • Spine Width: 21 mm
  • Width: 156 mm
  • ISBN-10: 3319739506
  • Publisher Date: 14 May 2018
  • Binding: Hardback
  • Height: 234 mm
  • No of Pages: 334
  • Series Title: Advances in Information Security
  • Weight: 707 gr


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