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, Çin, 15 - 18 Temmuz 2018, ss.262-269 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/icwapr.2018.8521252
  • Basıldığı Şehir: Chengdu
  • Basıldığı Ülke: Çin
  • Sayfa Sayıları: ss.262-269
  • Recep Tayyip Erdoğan Üniversitesi Adresli: Hayır

Özet

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.