Volume : IV, Issue : IV, April - 2014

Multi–Level Security System for Anomaly Detection–in Cloud Based Data

J. Jabez, Dr. G. S. Anandha Mala

Abstract :

 In recent years, the Data mining is an essential technique, audit the data by themselves and mine it, and also can be used for intrusion detection. Statistics [Mathematical Analization], ANN– Artificial Neural Network, HMM–Hidden Markov Model, and SVM – Support Vector Machine] are some of the main Data Mining (DM) techniques often used for anomaly and misbehavior detection and these techniques don’t have a proper scientific methodology to increase the efficiency of the intrusion detection. Thiswork is a novel approach named MLSS  [Multi Level Security System] is proposed for detecting the intruders in the cloud accurately and fast in each level of the Cloud Model. The Cloud Model is defined as Cloud Server, Cloud Engine, Cloud Storage, Cloud Platform, Cloud Software and Cloud Tester. The anomaly can be detected in each model of the cloud by configuring the Software as well as deploying software in the cloud. The experimental result shows the accuracy and efficiency of the MLSS where it is developed in VS2010 Professional Edition integrated with Visual Guard Admin Console.

 

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Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

Jabez Jones Multi-Level Security System for Anomaly Detectionin Cloud Based Data Indian Journal of Applied Research, Vol.IV, Issue. IV

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