Artificial Intelligence for Cyber Security Applications

The recent White House report on artificial intelligence (AI) highlights the importance of AI and the need for a clear roadmap and strategic investment in this area. As AI emerges from science fiction to become the frontier of world-changing technologies, there is an urgent need to systematically develop and implement AI to see its real impact in diverse fields of study.

This paper offers a contribution to the deployment of AI in the cybersecurity context. Intrusion detection has been the subject of numerous studies in industry and academia, but cybersecurity analysts still want a greater accuracy and comprehensive threat analysis to secure their systems in cyberspace. Improvements to intrusion detection could be achieved by adopting a more comprehensive approach to monitoring security events from many heterogeneous sources. Merging security events from heterogeneous sources and learning from data can offer a more holistic view and a better knowledge of the cyber threat situation. A problem with this approach is that at present even a single event source (for example, network traffic) can encounter big data challenges when it is considered alone. Attempts to use more heterogeneous data sources pose far greater challenges. Artificial Intelligence and Big Data Technologies can help solve these heterogeneous data Problems.

The proposed approach includes the pre-processing of data and learning. The experimental results show the effectiveness of the approach in terms of accuracy and detection rate and prove that Artificial Intelligence can help achieve better results in the Cyber Security context.