Now showing items 1-10 of 10

    • 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 ...
    • Enhanced Classification Accuracy on Naive Bayes Data Mining Models 

      Rahman, Chowdhury Mofizur; Kabir, Md. Faisal; Hossain, Alamgir; Dahal, Keshav (International Journal of Computer Applications, 2011-08-01)
      A classification paradigm is a data mining framework containing all the concepts extracted from the training dataset to differentiate one class from other classes existed in data. The primary goal of the classification ...
    • Face recognition in the Edge Cloud 

      Muslim, Nasif; Islam, Salekul (ACM, 2017-07)
    • 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. ...
    • A New Approach for Compressing Color Images using Neural Network 

      Rahman, Chowdhury Mofizur; Rahman, A. K. M. Ashikur (CIMCA, 2003-02-14)
      In this paper a neural network based image compression method is presented. Neural networks offer the potential for providing a novel solution to the problem of data compression by its ability to generate an internal data ...
    • On the Power of Feature Analyzer for Signature Verification 

      Rahman, Chowdhury Mofizur; Mahmud, Jalal Uddin (IEEE, 2012-12-06)
      This paper is concerned with verification of signatures using feature analysis and non linear classifier. Signatures are collected and scanned to obtain input image. Preprocessing involves removal of noise and making the ...
    • Secured Electronic Health Record Management Protocol 

      Islam, Salekul; Farzana, Syeda (ACM, 2017-07-26)
      Since digitization is now a common practice for storing and retrieving data, Electronic Health Record (EHR) management is becoming very popular. EHR management will bring many benefits including easy to store, cost effective, ...
    • A Survey on Multicasting in Software-Defined Networking 

      Islam, Salekul; Muslim, Nasif; Atwood, J William (IEEE Communications Surveys & Tutorials, 2017-11-23)
      Existing surveys of research into Software-Defined Networking (SDN) make only minimal mention of multicasting. We present a survey of existing multicast routing protocols in IP multicast, and a survey of existing and ...