Proceeding of

NCAICN National Conference 2013

(NCAICN-2013)

on

Advances in

Computing & Networking

as

A Special Issue of

International Journal of Computer Science and Applications

(ISSN:0974-1011)

Patron

Hon. Shri Sundeepji Meghe

(Chairman, Vidarbha Youth Welfare Society, Amravati)

 

Advisor

Dr. V.T. Ingole (FIE, FIETE, Professor Emeritus)

 

Organizing Committee

Chairman

Dr. D.T. Ingole (FIE, FIETE)

(Principal PRMIT & R, Badnera and  Chairman IEI  Amravati Center).

Secretary

 Er. A.W. Jawanjal

(Honorary Secretary IEI, Amravati Center)

Conveners

Dr. G.R. Bamnote ((FIE, FIETE)

(H.O.D. Computer Science & Engineering)

Dr. A.S. Alvi (MIE)

(H.O.D. Information Technology))

Prof. Mrs. M.D. Ingole (FIE.MIETE)

(H.O.D. Electronics & Telecommunication)

Coordinators

Prof. S.V. Dhopte ((FIE, FIETE)

Prof. Ms. V.M. Deshmukh (FIE, FIETE)

Dr. S.W. Mohod  (FIE,FIETE)

Co-Coordinators

Dr. S.R. Gupta (MIE, MIETE)

Prof. S.V. Pattalwar ((FIE, FIETE)

Prof. M.D. Damahe

Members

Prof. Mrs. M.S. Joshi                

Dr. S.M. Deshmukh

Prof. V.U. Kale

Prof. S.S. Kulkarni

Prof. Ms. R.R. Tuteja

Prof. Ms. J.N. Ingole

Prof. V.R. Raut

Prof. C.N. Deshmukh

Prof. Ms. M.S. Deshmukh

Prof. S.P. Akarte

Prof. Mrs. A.P. Deshmukh

Prof. Mrs. S.S. Sikchi

Prof. N.N. Khalsa

Department of Information and Computer Science and Engineering

Prof. Ram Meghe Institute of Technology and Research, Badnera Distt. Amravati

 

Editor

Prof. K. H. Walse

M.S.India
 

 

 

   
   
   
   
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
  
IJCSA ISSN: 0974-1011 (Online) >>    
Title:

Auto Detection of Attacks on Network

Author:
 Anup G. Kadu and Dr. A.S.Alvi
 
Abstract

The two knowledge-based approaches are not sufficient to tackle the anomaly detection problem, and that a holistic solution should also include knowledge-independent analysis techniques. There are some algorithms, and it becomes critical in the case of unsupervised detection, because there is no additional information to select the most relevant set some approaches can be easily extended to detect other types of attacks, considering different sets of traffic features. In fact, more features can be added to any standard list to improve detection and characterization results. The of Knowledge Independent Detection of Network Attack is simply to detect the attacks which are completely unknown to us. There is no previous knowledge about that data. There are some algorithms in existence which are used for network security but they are inefficient as they are knowledge based (Signature Based and Anomaly Based) whenever there is a vast amount of continuous incoming data then it is a big risk regarding the network attacks which are knowledge based. Our particular goal is to identify those attacks with the help of Robust Clustering Algorithm and make whole data secure.

©2013 International Journal of Computer Science and Applications 

Published by Research Publications, India