Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Network Intrusion Detection: Taxonomy and Machine Learning Applications.- Machine Learning and Deep Learning models for Big Data Issues.- The Fundamentals and Potential for Cybersecurity of Big Data in the Modern World.- Improving Cyber-Threat Detection by Moving the Boundary around the Normal Samples.- Bayesian Networks for Online Threat Detection.- Network Intrusion Detection for TCP/IP Packets with Machine Learning Techniques.- Developing a Blockchain-based and Distributed Database-oriented Multi-Malware Detection Engine.- Classifying Common Vulnerabilities and Exposures Database Using Text Mining and Graph Theoretical Analysis.- Robust Cryptographical Applications for a Secure Wireless Network Protocol.