| |
| |
|
|
|
|
| Packet Payload Inspection Classifier in the Network Flow Level
|
|
Full
text: |
PDF(379.9KB) |
|
|
Source |
International Journal of Computer Networks (IJCN) |
|
Table of Contents |
|
|
Download
Complete Issue PDF(666.85KB) |
|
Volume: 4 Issue: 3 |
| |
Pages: |
|
Publication
Date: June 2012 |
|
ISSN
(Online): 1985-4129 |
|
|
|
|
|
Pages |
53 - 71 |
|
Author(s) |
|
|
|
Published
Date |
20-06-2012 |
|
Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
|
ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
| |
|
| |
KEYWORDS: Flow Classification, Packet Inspection, Traffic Classification, Packet Processing, Bloom Filter |
|
|
| |
|
|
| No
record found |
| |
|
| |
|
|
| The network have in the world highly
congested channels and topology which was
dynamically created with high risk. In this we need
flow classifier to find the packet movement in the
network. In this paper we have to be developed and
evaluated TCP/UDP/FTP/ICMP based on payload
information and port numbers and number of flags
in the packet for highly flow of packets in the
network. The primary motivations of this paper all
the valuable protocols are used legally to process
find out the end user by using payload packet
inspection, and also used evaluations hypothesis
testing approach. The effective use of tamper
resistant flow classifier has used in one network
contexts domain and developed in a different
Berkeley and Cambridge, the classification and
accuracy was easily found through the packet
inspection by using different flags in the packets.
While supervised classifier training specific to the
new domain results in much better classification
accuracy, we also formed a new approach to
determine malicious packet and find a packet flow
classifier and send correct packet to destination
address. |
| |
|
| |
|
| |
| 1 |
W. Li and A. Moore. A machine learning approach for efficient traffic classification.In Proc.IEEE MASCOTS, 2007. |
|
|
| 2 |
utorrent.http://utorrent.en.softonic.com/. |
|
|
| 3 |
Wireshark Wireshark go deep.http ://www. wireshark.org/. |
|
|
| 4 |
“Skype testbed traces,” [Online]. Available: http://tstat.tlc.polito.it/ traces-skype.shtml |
|
|
| 5 |
A. W. Moore and D. Zuev, “Internet traffic classification using bayesian analysis techniques” in Proc.ACM SIGMETRICS, Banff, Canada,Jun. 2005, pp. 50–60. |
|
|
| 6 |
N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and Kernel-Based Learning Methods. New York: Cambridge Univ. Press, 1999. |
|
|
| 7 |
S. Dharmapurikar and J. Lockwood, “Fast and Scalable Pattern Matching for Network Intrusion Detection Systems,” IEEE J. Selected Areas in Comm., vol. 24, no. 10, pp.1781-1792, Oct. 2006. |
|
|
| 8 |
W.-C.F.F.Chang and K. Li,“ApproximateCaches for Packet Classific ati on ,”Proc.IEEE INFOCOM ’04, vol. 4, pp. 2196-2207, Mar. 2004. |
|
|
| 9 |
H.C. Deke Guo, J. Wu, and X. Luo,“Theory and NetworkApplications of Dynamic Bloom Filters,”Proc.IEEE INFOCOM’06,pp. 1233-1242, 2006. |
|
|
| 10 |
M.Waldvogel, G.Varghese, J.Turner, and B.Plattner,“Scalable High Speed IP Routing Lookups,”Proc.ACM SIGCOMM’97,pp. 25-36, 1997. |
|
|
| 11 |
I. Kaya and T. Kocak, “Energy-Efficient Pipelined Bloom Filters for Network Intrusion Detection,” Proc. IEEE Int’l Conf. Comm.,pp. 2382-2387, 2006. |
|
|
| 12 |
J.T. Sailesh Kumar and P. Crowley,Peacock Hashing: Deterministic and Updatable Hashing for High Performance Networking,”Proc. IEEE INFOCOM ’08, pp. 101-105, 2008. |
|
|
| 13 |
S.Kumar and P.Crowley,“Segmented Hash:An Efficient Hash Table Implementation for High Performance Networking Subsystems,” Proc. ACM Symp. Architecture for Networking and Comm.Systems (ANCS ’05), pp. 91-103, 2005 |
|
|
| 14 |
S. Dharmapurikar, P. Krishnamurthy, and D.E. Taylor, “Longest Prefix Matching Using Bloom Filters,” Proc. SIGCOMM ’03, pp. 201-212, 2003. |
|
|
| 15 |
T.S.SarangDharmapurikar,P.Krishnamurthy,andJ.Lockwood,“Deep Packet Inspection Using Parallel Bloom Filters,”Proc. 37th Ann. AC M/IEEEI nt’lSymp . Microarchitectuepp.52-61, 2004. |
|
|
| 16 |
H. Song, J. Turner, and S. Dharmapurikar, “Packet Classification Using Coarse-Grained Tuple Spaces,” Proc. ACM/IEEE Symp.Architecture for Networking and Comm. Systems (ANCS ’06), pp. 41-50, 2006. |
|
|
| 17 |
M. Mitzenmacher and S. Vadhan, “Why Simple Hash Functions Work: Exploiting the Entropy in a Data Stream,” Proc. 19th Ann.ACM-SIAMSymp.Discrete Algorithms (SODA ’08), pp. 746-755, 2008. |
|
|
| 18 |
B. Dipert, “Special Purpose SRAM Smooth the Ride,” June 1999. |
|
|
| 19 |
ACTIhttp://www.hpl.hp.co.uk/personal/Norm an_Jouppi/cacti5.html,2010 |
|
|
| 20 |
D.A. Patterson and J.L. Hennessy, Computer Architecture: A Quantitative Approach,Morgan Kaufmann Publishers Inc., 1990. |
|
|
| 21 |
S. Dharmapurikar, P. Krishnamurthy,and D.E. Taylor, “Longest Prefix Matching Using Bloom Filters,” Proc. SIGCOMM’03, pp. 201-212, 2003. |
|
|
| 22 |
CACTI.http://www.hpl.hp.co.uk/persl/Nor an Jouppi/ cacti5.html, 2010. |
|
|
| 23 |
Tian Song, Wei Zhang, Dongsheng Wang,Yibo Xue, A Memory Efficient Multiple Pattern Matching Architecture for Network Security.Proceedings of IEEE Infocom, 2008 |
|
|
| 24 |
Jan.van.Lunteren,High performance pattern matching for intrusion detection.Proceedings of Infocom’06, 2006. |
|
|
| 25 |
Hongbin Lu, Kai Zheng, Bin Liu, Xin Zhang, and Yunhao Liu, A Memory-Efficient Parallel String Matching Architecture for High- Speed Intrusion Detection. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS,VOL.24,NO.10,OCTOBER 2006 |
|
|
| 26 |
L. Fan, P. Cao, J. Almeida, and A.Z. Broder, “Summary Cache: A Scalable Wide-Area Web Cache Sharing Protocol,” IEEE/ACM Trans. Networking, vol. 8, no. 3, pp. 281- 293,June 2000. |
|
|
| |
|
| |
|
| |
| |
|
| |
|
| |
| |
|
| |
|
| |
|
| N. Kannaiya Raja : Colleagues
|
|
| K.Arulanandam : Colleagues
|
|
| P. Umadevi : Colleagues
|
|
| D.S.Praveen : Colleagues
|
|
|
|
|
|
|
|
|
|
|