A Network Attack Classification for Multi Agent System Using Flow Based Intusion Detection System

Abstract

Intrusion detection system is precious for protecting the entire network from a large range of threats, modern intrusion detection techniques must cope with not only increase the detection rate but also increase the speed of the network line, signature based ids forced to sample meagerly, increasing the probability of harmful traffic flowing towards the network without inspection subsequently, flow based id is attaining awareness as an effective complement. Basically ids are classified in to network based or host based The independent multi agent design idea is a scalable, striking option for its potential to influence the strengths of both architectures: the broad perspective and visibility into distributed harmful activity provided by network-based ID, and the complete view of the local node provided by host-based ID. This paper develops an architecture for an new multi agent, flow based intrusion detection system. The architecture is designed in two iterations of increasing complexity. These innovative designs are used to find nodes by “reputation “concept that are most effective for classifying harmful network activity. Every system has to design which includes the growth of an innovative classifier that uses multi point evolutionary algorithms to assist in the search for efficient functioning parameter values. Extensive agent simulation framework which highlights the condition under the Reputation System provides a Classification.

Authors and Affiliations

K. A. VarunKumar| Department of Computer Science and Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai, S. Sibi Chakkaravarthy| Department of Computer Science and Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai, G. Saravanan| Department of Information Technology, Department of Electrical & Electronics Engineering Vel Tech Dr. RR & Dr.SR Technical University, Chennai, V. Vetriselvan| Department of Information Technology, Department of Electrical & Electronics Engineering Vel Tech Dr. RR & Dr.SR Technical University, Chennai, P. Dharani| Department of Information Technology, Department of Electrical & Electronics Engineering Vel Tech Dr. RR & Dr.SR Technical University, Chennai, C. Aravind| Department of Information Technology, Department of Electrical & Electronics Engineering Vel Tech Dr. RR & Dr.SR Technical University, Chennai

Keywords

Related Articles

Unstructured Multidimensional Array Multimedia Retrival Model based XML Database

Unstructured Data derived from the thought of data warehouse, data cube and xml, this paper presents a new database structure model which organizes the unstructured data in a multidimensional data cube based on XML D...

Ship Detection with Wireless Sensor Network

The main aim of this work is an Intrusion detection on the sea which is a critical surveillance problem for harbor protection, border security, and also the protection of business facilities, such as oil platforms and...

Insilico Analysis & 3D Structure Prediction of Hemagglutinin Protein of H9N2 Avian Influenza Virus

H9N2 avian influenza virus are widespread in chickens,quail and other poultry in asia and have caused a few cases of influenza in humans. To understand the structural and functional analysis of H9N2 avian influenza v...

An Automated Multi Sensored Green House Management

The main objective of our work is to design an automated agricultural system which is purely sensor based and economical as well as durable and with the best success rate which can manage everything without the human...

Sub-threshold Logic for Ultra-Low Power Consumption

In the ultra low power end of design spectrum when performance is of secondary importance, digital subthreshold logic circuits are more applicable than the regular MOS logic. In this paper, we propose two different su...

Download PDF file
  • EP ID EP8488
  • DOI -
  • Views 377
  • Downloads 23

How To Cite

K. A. VarunKumar, S. Sibi Chakkaravarthy, G. Saravanan, V. Vetriselvan, P. Dharani, C. Aravind (2013). A Network Attack Classification for Multi Agent System Using Flow Based Intusion Detection System. The International Journal of Technological Exploration and Learning, 2(5), 181-187. https://europub.co.uk/articles/-A-8488