Cyber Threat Intelligence

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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• Inteligência artificial
• Segurança do computador
• Redes de computadores e comunicações
• Robótica
• Hardware de rede

Cyber threat;Cyber security;Hacking;Threat intelligence;Machine learning;cyber forensics;threat analysis;intrusion detection;incident response;cyber defense;malware analysis;malware campaign detection;cyber kill chain;indicators of compromise;evidence correlation