Recently, the GIAC GCIA Gold Paper I have been working on for 6 months got approved and published in the SANS Reading Room. This is the first of two papers I aim to publish before I reach the end of University, with the other hopefully coming soon!
It focused on the application of machine learning and big data techniques to the intrustion detection sector to automatically detect common attack surfaces. The abstract and link to the paper can be seen below:
“With almost 40% of UK businesses experiencing a cyber-attack in 2020, the need for accurate and rapid detection of attacks is evident. However, traditional signature-based IDS systems are inefficient at detecting advanced threats due to the time involved in verifying and distributing signatures. Similarly, first-generation SIEM systems show limitations when processing big data, and sophisticated attacks go undetected. This paper introduces and explores large-scale data analysis and machine learning tools within intrusion detection.”
If you would like to read the full paper, click here.