Now showing items 1-4 of 4

    • An Adaptive Ensemble Classifier for Mining Concept-Drifting Data Streams 

      Rahman, Chowdhury Mofizur; Farid, Dewan Md; Zhang, Li; Hossain, Alamgir; Strachan, Rebecca; Sexton, Graham; Dahal, Keshav (Expert Systems with Applications, 2013-11-01)
      Traditional data mining techniques cannot be directly applied to the real-time data streaming environment. Existing mining classifiers therefore need to be updated frequently to adopt the changes in data streams. In this ...
    • Adaptive Intrusion Detection based on Boosting and Naïve Bayesian Classifier 

      Rahman, Chowdhury Mofizur; Farid, Dewan Md; Rahman, Mohammad Zahidur (International Journal of Computer Applications, 2011-06-01)
      In this paper, we introduce a new learning algorithm for adaptive intrusion detection using boosting and naïve Bayesian classifier, which considers a series of classifiers and combines the votes of each individual classifier ...
    • Attacks classification in adaptive intrusion detection using decision tree 

      Rahman, Chowdhury Mofizur; Farid, Dewan Md; Harbi, Nouria; Bahri, Emna; Rahman, Mohammad Zahidur (World Academy of Science, Engineering and Technology, 2010-03-22)
      Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems ...
    • Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks 

      Rahman, Chowdhury Mofizur; Farid, Dewan Md; Hossain, M Alamgir; Strachan, Rebecca (Expert Systems with Applications, 2014-03-31)
      In this paper, we introduce two independent hybrid mining algorithms to improve the classification accuracy rates of decision tree (DT) and naïve Bayes (NB) classifiers for the classification of multi-class problems. ...