Predictive Cyber Threat Analysis using Data Science: An Overview of Possibilities (in English)
Synopsis "Predictive Cyber Threat Analysis using Data Science: An Overview of Possibilities (in English)"
Data Science methods can be applied to any imaginable goal and offer insight into how to progress from the status quo to a much higher level of cyber security. This short book addresses some of the possible approaches to applying data science to security needs, how to identify open source tools, and how to potentially implement visualization and statistical analysis for use in the area of Predictive Cyber Threat Analysis. Because of the vast amount of data that is produced by modern networks, novel methods and techniques are needed to predict cyber threats. The landscape of current threats requires new analysis methods. This paper explores how data science and visualization tools and technology aid in this mission; allowing the naked eye to detect patterns and obtain insight into our networks. This paper investigates the options available to security engineers, analysts, and investigators for exploiting "big data." We question: -How is Data Science used to predict cyber threats? What are open source tools available for statistical analysis? -What methods provide the best visual representation of our analysis? By developing an understanding of big data, we can adapt to meet the rapid and ever-evolving cyber threat to our national security. Once understood, training, tools, and processes can be implemented in cyber threat analysis. Our purpose is to help organizations; to develop, a basic understanding of data science, to identify possible tools to used to in data science and security, and finally to focus on applications that can be used to target cyber threats. "The state of information security is in disarray." (Braxton, 2015). Groups from every industry are failing to detect attacks. A primary cause of today's failures in both security prevention and detection is the ever-increasing amount of data that networks must process. Data immersion is not a new concept. Experts agree that the phenomenon is accelerating. "Lakes, puddles, and rivers of data have turned to floods and veritable tsunamis of structured, semi-structured, and unstructured data that's streaming from almost every activity that takes place in both the digital and physical worlds" (Pierson, 2015). This is big data, and it is only getting bigger. Keywords: Data Science, Security, cognitive science, Open Source, visualization, threat analysis, threat intelligence.
