FEATURE ANALYSIS ON THE CONTAINMENT TIME FOR CYBER SECURITY INCIDENTS


Akkuzu G. , Aziz B., Liu H.

International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), Chengdu, China, 15 - 18 July 2018, pp.262-269 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/icwapr.2018.8521252
  • City: Chengdu
  • Country: China
  • Page Numbers: pp.262-269

Abstract

Data mining techniques have been widely used as a common goal to discover hidden patterns from big data sets, so researchers have been motivated to make use of data in discovering useful information. The main contribution of this paper lies in its identifying relevant features from an open data set to predict the containment time of Cyber incidents. In particular, 13 relevant features were identified and selected to come up with a predictive model. Our results are discussed in the context of the organization's' information security.