Bayesian Classifier and Snort based network intrusion detection system in cloud computing

One of the major security issues in cloud computing is to protect against network intrusions that affect confidentiality, availability and integrity of Cloud resources and offered services. To address this issue, we design and integrate Bayesian Classifier and Snort based network intrusion detection system (NIDS) in Cloud. This framework aims to detect network intrusions in Cloud environment with low false positives and affordable computational cost. To ensure feasibility of our NIDS module in Cloud, we evaluate performance and quality results on KDD'99 experimental dataset.

[1]  R. Chitra,et al.  Securing cloud from ddos attacks using intrusion detection system in virtual machine , 2013 .

[2]  R. Geetha Ramani,et al.  Discriminant Analysis based Feature Selection in KDD Intrusion Dataset , 2011 .

[3]  Christoph Meinel,et al.  An Extensible and Virtualization-Compatible IDS Management Architecture , 2009, 2009 Fifth International Conference on Information Assurance and Security.

[4]  Dinesh Sequeira.  INTRUSION PREVENTION SYSTEMS - SECURITY'S SILVER BULLET? , 2002 .

[5]  Roberto Bifulco,et al.  Integrating a network IDS into an open source Cloud Computing environment , 2010, 2010 Sixth International Conference on Information Assurance and Security.

[6]  Kamalrulnizam Abu Bakar,et al.  Distributed Intrusion Detection in Clouds Using Mobile Agents , 2009, 2009 Third International Conference on Advanced Engineering Computing and Applications in Sciences.

[7]  Chi-Chun Lo,et al.  A Cooperative Intrusion Detection System Framework for Cloud Computing Networks , 2010, 2010 39th International Conference on Parallel Processing Workshops.

[8]  Aman Bakshi,et al.  Securing Cloud from DDOS Attacks Using Intrusion Detection System in Virtual Machine , 2010, 2010 Second International Conference on Communication Software and Networks.

[9]  T. Karthikeyan,et al.  Outlier Removal Clustering through Minimum Spanning Tree , 2011 .

[10]  N. Balakrishnan,et al.  Performance enhancement of Intrusion Detection Systems using advances in sensor fusion , 2008, 2008 11th International Conference on Information Fusion.

[11]  Rung Ching Chen,et al.  Using Rough Set and Support Vector Machine for Network Intrusion Detection System , 2009, 2009 First Asian Conference on Intelligent Information and Database Systems.