%0 Journal Article %1 kmuthumanickameilavarasan2014dynamic %A K.Muthumanickam, E.Ilavarasan, Sanjeev Kumar Dwivedi %D 2014 %E Hope, Dr.Martin %J Int. J. on Recent Trends in Engineering and Technology, %K Bots_P2P botnet_In-out degree %N 1 %P 8 %T A Dynamic Botnet Detection Model based on Behavior Analysis %U http://searchdl.org/public/journals/2014/IJRTET/10/1/18.pdf %V 10 %X Today different types of malware exist in the Internet. Among them one of the malware is known as botnet which is frequently used for many cyber attacks and crimes in the Internet. Currently botnets are the main rootcause for several illegal activities like spamming, DDoS, click fraud etc. Botnets operate under the command and control(C&C) infrastructure which makes its functioning unique. As long as the Internet exists botnet also will exist. It can be used to perpetrate many Internet crimes. So fighting against them is a challenging problem. The P2P-decentralized based botnets are more dangerous than centralized botnets. In this paper a novel approach for the detection of P2P based botnet is presented. The proposed approach for the detection of botnet in the network stream analysis has been done in three phases. The first phase begins with the identification of P2P node and the second phase deals with the clustering of the suspicious P2P node. Finally botnet detection procedure has been applied which is based on stability of bots. Experimental results show that the proposed approach detects more number of bots with high accuracy.

@article{kmuthumanickameilavarasan2014dynamic, abstract = {Today different types of malware exist in the Internet. Among them one of the malware is known as botnet which is frequently used for many cyber attacks and crimes in the Internet. Currently botnets are the main rootcause for several illegal activities like spamming, DDoS, click fraud etc. Botnets operate under the command and control(C&C) infrastructure which makes its functioning unique. As long as the Internet exists botnet also will exist. It can be used to perpetrate many Internet crimes. So fighting against them is a challenging problem. The P2P-decentralized based botnets are more dangerous than centralized botnets. In this paper a novel approach for the detection of P2P based botnet is presented. The proposed approach for the detection of botnet in the network stream analysis has been done in three phases. The first phase begins with the identification of P2P node and the second phase deals with the clustering of the suspicious P2P node. Finally botnet detection procedure has been applied which is based on stability of bots. Experimental results show that the proposed approach detects more number of bots with high accuracy.}, added-at = {2014-02-01T07:22:36.000+0100}, author = {{K.Muthumanickam, E.Ilavarasan}, Sanjeev Kumar Dwivedi}, biburl = {https://www.bibsonomy.org/bibtex/2e0165b52a9af723134f1d2637b7fa0a8/idescitation}, editor = {Hope, Dr.Martin}, interhash = {652fcdcd2779e1e7194354e34a68657f}, intrahash = {e0165b52a9af723134f1d2637b7fa0a8}, journal = {Int. J. on Recent Trends in Engineering and Technology,}, keywords = {Bots_P2P botnet_In-out degree}, month = {Jan 2014}, number = 1, pages = 8, timestamp = {2014-02-01T07:22:36.000+0100}, title = {A Dynamic Botnet Detection Model based on Behavior Analysis}, url = {http://searchdl.org/public/journals/2014/IJRTET/10/1/18.pdf}, volume = 10, year = 2014 }