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An Efficient Clustering Scheme to Exploit Hierarchical Data in Network Traffic Analysis.

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Presentation on theme: "An Efficient Clustering Scheme to Exploit Hierarchical Data in Network Traffic Analysis."— Presentation transcript:

1 An Efficient Clustering Scheme to Exploit Hierarchical Data in Network Traffic Analysis

2 Abstract There is significant need to improve existing techniques for clustering multivariate network traffic flow record and quickly infer underlying traffic patterns. There is significant need to improve existing techniques for clustering multivariate network traffic flow record and quickly infer underlying traffic patterns. we investigate the use of clustering techniques to identify interesting traffic patterns from network traffic data in an efficient manner. we investigate the use of clustering techniques to identify interesting traffic patterns from network traffic data in an efficient manner. A framework is developed to deal with mixed type attributes including numerical, categorical, and hierarchical attributes. A framework is developed to deal with mixed type attributes including numerical, categorical, and hierarchical attributes. We demonstrate the improved accuracy and efficiency of our approach in clustering network traffic. We demonstrate the improved accuracy and efficiency of our approach in clustering network traffic.

3 Existing System Categorization based Network monitoring (Auto Focus) techniques. Categorization based Network monitoring (Auto Focus) techniques. Traffic matrix: The aim of traffic matrix measurement is to estimate the volume of traffic between origin and destination points in the network for capacity planning. Traffic matrix: The aim of traffic matrix measurement is to estimate the volume of traffic between origin and destination points in the network for capacity planning. Traffic volume: The aim of traffic volume measurement is to determine the total traffic sent or received in a network. Of particular interest is the problem of measuring network usage of customers. Traffic volume: The aim of traffic volume measurement is to determine the total traffic sent or received in a network. Of particular interest is the problem of measuring network usage of customers. Traffic dynamics: The aim of monitoring traffic dynamics is to measure the temporal variation in Internet traffic. Traffic dynamics: The aim of monitoring traffic dynamics is to measure the temporal variation in Internet traffic. Traffic mixture: when traffic volume data is aggregated over time, it can reveal important features of network usage for performance and security management. Traffic mixture: when traffic volume data is aggregated over time, it can reveal important features of network usage for performance and security management.

4 Disadvantages It does not has Hierarchical Classification It does not has Hierarchical Classification DOS Attacker can not be Found DOS Attacker can not be Found No Intimation for any violation No Intimation for any violation

5 Proposed System Hierarchical, distance-based clustering scheme (Echidna). Hierarchical, distance-based clustering scheme (Echidna). To summarize the main types of traffic flows that are observed in a network. To summarize the main types of traffic flows that are observed in a network. Introduction of a new distance measure for hierarchically structured attributes such as IP addresses and a set of heuristics. Introduction of a new distance measure for hierarchically structured attributes such as IP addresses and a set of heuristics. Summarize and compress reports of significant traffic clusters from a hierarchical clustering algorithm. Summarize and compress reports of significant traffic clusters from a hierarchical clustering algorithm.

6 Advantages It has System based Hierarchical Classification It has System based Hierarchical Classification Efficient Network Traffic Monitoring Efficient Network Traffic Monitoring Infer of underlying patterns for multivariate traffic flows Infer of underlying patterns for multivariate traffic flows It Identify DOS Attack It Identify DOS Attack

7 Modules Tree construction Tree construction Traffic analysis Traffic analysis System classification System classification Network management Network management

8 Requirement Analysis SOFTWARE REQUIREMENTS:- Operating system :Windows XP Professional. Operating system :Windows XP Professional. Language Used:Java 1.6 (Swings,AWT,Sockets) Language Used:Java 1.6 (Swings,AWT,Sockets) Database:SQL Server 2000 Database:SQL Server 2000 HARDWARE REQUIREMENTS:- Hard disk:80 GB Hard disk:80 GB RAM:1 GB RAM:1 GB Processor:Pentium IV 3.3 GHz Processor:Pentium IV 3.3 GHz

9 THANK YOU


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