A New Cyber Security Alert System for Twitter

Erkal Y., Sezgin M., Gunduz S.

IEEE 14th International Conference on Machine Learning and Applications ICMLA, Florida, Amerika Birleşik Devletleri, 9 - 11 Aralık 2015, ss.766-770 identifier identifier

  • Cilt numarası:
  • Doi Numarası: 10.1109/icmla.2015.133
  • Basıldığı Şehir: Florida
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.766-770


This study proposes an autonomous early decision system for cyber security related contents of Twitter. In the context, both cyber and non-cyber security related tweets are collected and the obtained data is trained by means of Naive Bayes Classifier. Besides, Term Frequency - Inverse Document Frequency (TF-IDF) term weighting method is used for vectorization purpose. Experimental results show that, the developed system can classify the tweets in terms of their cyber security related or non-related security with the 70.03% success rate. It can be included that the system can be used as an alert system on Twitter for early cyber-attack detection.