Network Intrusion Detection System (NIDS) based on Data Mining

With the tremendous growth in information technology, network security is one of the challenging issue and so as Intrusion Detection system (IDS). IDS are an essential component of the network to be secured. The traditional IDS are unable to manage various newly arising attacks. To deal with these new problems of networks, data mining based IDS are opening new research avenues. Data mining is used to identify new patterns which were not known previously from large volume of network dataset. New Intrusion Detection Systems are based on sophisticated algorithms in spite of signature based detection. Data mining method uses binary classifiers and multiboosting simultaneously. Features are selected using binary classifiers for more accuracy in each type of attack. Multiboosting is used to reduce both the variance and bias. With data mining, it is easy to identify valid, useful and understandable pattern in large volume of data. Thus the efficiency and accuracy of Intrusion Detection system are increased and security of network so is also enhanced.

[1]  A. John,et al.  Survey on data mining techniques to enhance intrusion detection , 2012, 2012 International Conference on Computer Communication and Informatics.

[2]  Zulaiha Ali Othman,et al.  Network anomaly detection tools based on association rules , 2011, Proceedings of the 2011 International Conference on Electrical Engineering and Informatics.

[3]  Michael J. Shevenell,et al.  Design and Implementation of an Open Network and Host-Based Intrusion Detection Testbed with an Emphasis on Accuracy and Repeatability , 2012, 2012 Ninth International Conference on Information Technology - New Generations.

[4]  P. Prasenna,et al.  Network programming and mining classifier for intrusion detection using probability classification , 2012, International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012).

[5]  Wei Chen,et al.  A study of intrusion detection system based on data mining , 2010, 2010 IEEE International Conference on Information Theory and Information Security.

[6]  Ye Qing,et al.  An intrusion detection approach based on data mining , 2010, 2010 2nd International Conference on Future Computer and Communication.

[7]  Ankit Fadia.  Network Intrusion Alert: An Ethical Hacking Guide to Intrusion Detection , 2007 .

[8]  S. K. Sharma,et al.  An improved network intrusion detection technique based on k-means clustering via Naïve bayes classification , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[9]  Wenjun Zeng,et al.  A New Data-Mining Based Approach for Network Intrusion Detection , 2009, 2009 Seventh Annual Communication Networks and Services Research Conference.

[10]  Ming Xue,et al.  Applied Research on Data Mining Algorithm in Network Intrusion Detection , 2009, 2009 International Joint Conference on Artificial Intelligence.

[11]  D. V. Ashoka,et al.  Data mining based network intrusion detection system: A database centric approach , 2012, 2012 International Conference on Computer Communication and Informatics.