Host Based Intrusion Detection System Using Decision Tree and Naïve Bayes Algorithms

Mr Abhijeet Mahadule, Mr Atul Rathod, Mr Shubham Singh, Mr Rahul B. Adhao

Abstract


A network intrusion is any unauthorized access to a computer network. For detecting a network intrusion, the defenders should have a clear understanding of how attacks work. In a network environment, intrusions possess a major security issue which can be an unauthorized activity on a computer network which is generally difficult to detect. Through this project we aim to monitor computer network for malicious activity using Intrusion Detection System (IDS). In this work, we aim to use Supervised Machine Learning Algorithms such as Naive Bayes Classifier and Decision Tree Classifiers, and compare their output and efficiency. The machine learning algorithms are used on a labelled dataset, which classifies the connections as good or bad. As a result, the accuracy of the classification result has to be maximized by maintaining low false-negative and low false-positive rates.


Full Text:

PDF

References


Harish C., Palash Chaturvedi, Amit K. Saxena, "A Systematic Literature Survey in IDS", International Journal on Recent and Innovation Trends in Computing and Communication, Vol 5,Issue:6, 2017

Sravan K. Jonnalagadda, Ravi P. Reddy, "A Literature Survey and Comprehensive Study of Intrusion Detection", International Journal of Computer Applications, Volume 81, 2013

Mrutyunjaya Panda, Manas R. Patra, "Network Intrusion detection using Naive Bayes", International Journal of Computer Science and Network Security, Vol 7, 2007

Gavin wolf,Dr.Taghi,M.Khoshgoftaar, “Using Machine Learning for Network Intrusion Detection: The Need for Representative Data”, Florida Atlantic University Boca Raton, Florida USA, May 2016

Suseela T., Q.A. Zhu, “Hierarchical Kohonenen net for anomaly detection in network security J.Huff”,IEEE Transactions on Sysytem,Man and Cybernatics,Part(B),Cybernatics ( Volume: 35, Issue:2, April 2005 )

Ajith Abraham, Sandhya Peddabachigari, C. Grosan, Johnson Thomas, "Modelling intrusion detection system using hybrid intelligent systems", Journal of Network and Computer Applications, 2007

Iwan Syarif, Adam Prugel-Bennett, Gary Wills, "Data Mining Approaches for Network Intrusion Detection: from Dimensionality Reduction to Misuse and Anomaly Detection", Journal of Information Technology, Vol 3, 2012

Therese R. Metcalf, Leonard J. LaPadula, "Intrusion Detection System Requirements: A Capabilities Description in terms of Network Monitoring and Assessment Module of CSAP21", MITRE, MP 00B0000046, 2000

Mukkamala, Andrew Sung, Ajith Abraham, "Designing Intrusion Detection Systems: Architectures, Challenges and Perspectives", Journal of Network and Computer Application, Vol 28, Issue 2, 2005

Dewan Md. Farid, Nouria Farbia and Mohammad Zahiur Rahman ,”Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection” International Journal of Network Security & Its Applications 2.2 (2010) 12-25


Refbacks

  • There are currently no refbacks.