• 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.

“Cyber Threat Intelligence offers responsible security professionals a chance to come face to face with the cyberthreat detectors of the modern era. Many may be intimidated by the ‘computerese,’ equations, and algorithms … but they have the educational advantage of engaging with the genuine article, not a sugar-coated primer.” (James T. Dunne, Security Management, June 01, 2019)

• 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.

“Cyber Threat Intelligence offers responsible security professionals a chance to come face to face with the cyberthreat detectors of the modern era. Many may be intimidated by the ‘computerese,’ equations, and algorithms … but they have the educational advantage of engaging with the genuine article, not a sugar-coated primer.” (James T. Dunne, Security Management, June 01, 2019)

• 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.

“Cyber Threat Intelligence offers responsible security professionals a chance to come face to face with the cyberthreat detectors of the modern era. Many may be intimidated by the ‘computerese,’ equations, and algorithms … but they have the educational advantage of engaging with the genuine article, not a sugar-coated primer.” (James T. Dunne, Security Management, June 01, 2019)