Proceeding of

NCAICN National Conference 2013



Advances in

Computing & Networking


A Special Issue of

International Journal of Computer Science and Applications



Hon. Shri Sundeepji Meghe

(Chairman, Vidarbha Youth Welfare Society, Amravati)



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


Organizing Committee


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

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


 Er. A.W. Jawanjal

(Honorary Secretary IEI, Amravati Center)


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)


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

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

Dr. S.W. Mohod  (FIE,FIETE)


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

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

Prof. M.D. Damahe


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



Prof. K. H. Walse





IJCSA ISSN: 0974-1011 (Online) >>    

Auto Detection of Attacks on Network

Anup G. Kadu and Dr. A.S.Alvi


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