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Detecting and Preventing Attacks Using Network Intrusion Detection Systems
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International Journal of Computer Science and Security (IJCSS)
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Volume:  2    Issue:  1
Pages:  1-86
Publication Date:   February 2008
ISSN (Online): 1985-1553
Pages 
49 - 60
Author(s)  
 
Published Date   
30-02-2008 
Publisher 
CSC Journals, Kuala Lumpur, Malaysia
ADDITIONAL INFORMATION
Keywords   Abstract   References   Cited by   Related Articles   Collaborative Colleague
 
KEYWORDS:   intruders, information security, real time IDS, attacks, signature 
 
 
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Intrusion detection is an important technology in business sector as well as an active area of research. It is an important tool for information security. A Network Intrusion Detection System is used to monitor networks for attacks or intrusions and report these intrusions to the administrator in order to take evasive action. Today computers are part of networked; distributed systems that may span multiple buildings sometimes located thousands of miles apart. The network of such a system is a pathway for communication between the computers in the distributed system. The network is also a pathway for intrusion. This system is designed to detect and combat some common attacks on network systems. It follows the signature based IDs methodology for ascertaining attacks. A signature based IDS will monitor packets on the network and compare them against a database of signatures or attributes from known malicious threats. It has been implemented in VC++. In this system the attack log displays the list of attacks to the administrator for evasive action. This system works as an alert device in the event of attacks directed towards an entire network. 
 
 
 
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3 Komninos T., Spirakis P.: Dare the Intruders, Ellinika Grammata and CTI Press (2003).
4 E. Biermann, E.Cloete, L.M. Venter, A comparison of Intrusion detection systems, Computers and Security, 20(2001)8, 676–683. [5] P. Ning and D. Xu. Hypothesizing and reasoning about attacks missed by intrusion detection systems. ACM Transactions on Information and System Security, 7(4):591– 627, November 2004
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8 R.G. Bace, Intrusion Detection. Macmillan Technical Publishing, 2000
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10 Patwardhan, A. Parker, J., Joshi,A., Karygiannis, A., and Iorga,M. “Secure Routing and Intrusion Detection in Ad Hoc Networks”, Third IEEE International Conference on Pervasive Computing and Communications, Kauai Island, Hawaii, 2005.
11 http://www.winpcap.org/ - Obtained drivers for packet capture with wpcap.dll and packet.dll driver.
12 http://www.karalon.com - Obtained Karalon IQ professional tool for testing our network intrusion detection system.
13 http://www.securityfocus.com – White papers for intrusion detection techniques and methodologies.
14 R. Lippmann, The Role of Network Intrusion Detection, In Proceedings of the Workshop on Network Intrusion Detection, H.E.A.T. Center, Aberdeen, MD, March 19-20, 2002.
15 SNORT Intrusion Detection System, www.snort.org, 2004.
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18 Cisco Systems, Inc., NetRanger-Enterprise-scale, Real-time, Network Intrusion Detection System, http://www.cisco.com/univercd/cc/td/doc/product/iaabu/netrangr/, 1998.
19 Internet Security Systems, Inc., RealSecure, http://www.iss.net/prod/rsds.html, 1997.
20 Intrusion.com, Intrusion SecureHost, white paper available at: www.intrusion.com/products/hids.asp , 2003.
21 J. Van Ryan, SAIC's Center for Information Security, Technology Releases CMDS Version 3.5, http://www.saic.com/news/may98/news05-15-98.html, 1998.
22 N. Weaver, V. Paxson, S. Staniford and R. Cunningham, A Taxonomy of Computer Worms, In Proceedings of the The Workshop on Rapid Malcode (WORM 2003), held in conjunction with the 10th ACM Conference on Computer and Communications Security, Washington, DC, October 27, 2003.
23 Wheel Group Corporation, Cisco Secure Intrusion Detection System, http://www.cisco.com/univercd/cc/td/doc/product/iaabu/csids/index.htm , 2004
24 P. Ning and D. Xu. Hypothesizing and reasoning about attacks missed by intrusion detection systems. ACM Transactions on Information and System Security, 7(4):591– 627, November 2004
 
 
 
1 S. Karthik, V. P. Arunachalam and T. Ravichandran, “A Novel Direction Ratio Sampling Algorithm (DRSA) Approach for Multi Directional Geographical Traceback”, International Journal of Computer Science and Security (IJCSS), 3(4), pp. 272 - 279, 2009.
2 L. Gheorghe, R. Rughinis and N. Tapus, “Attack Evaluation and Mitigation Framework”, in Proceedings, Networking and Services (ICNS), 2010 Sixth International Conference , Cancun, 7-13 March 2010, pp. 243 – 252.
3 S. P. T. Vinay and A. Shanmugam, “Behavior Based Anomaly Detection Technique to Mitigate the Routing Misbehavior in MANET”, International Journal of Computer Science and Security (IJCSS), 3(2), pp. 62 – 75, 2009.
4 4. Z.Muda, W.Yasin, M.N.Sulaiman and N.I.Udzir, “A K-Means and Naive Bayes Learning Approach for Better Intrusion Detection” International Technology Journal, 10(3), pp. 648-656, 2011.
5 E. Nikolova and V. Jecheva, “Anomaly Based Intrusion Detection Using Data Mining and String Metrics”, in Proceedings of Communications and Mobile Computing, CMC '09. WRI International Conference , Yunnan, 6-8 Jan. 2009, pp. 440 – 444.
6 A. S. Hosam, A. Mustafa, S. Ahmad and M. Abbas, “Exception Agent Detection System for IP Spoofing Over Online Environments”, International Journal of Computer Science and Information Security, 6(1), pp. 158-164, 2009.
7 C. Manusankar, S. Karthik and T. Rajendran, “Intrusion Detection System with Packet Filtering for IP Spoofing”, in Proceedings of Communication and Computational Intelligence (INCOCCI), 2010 International Conference, Erode, 27-29 Dec. 2010, pp. 563 – 567.
 
 
 
1 MENDELEY
 
 
 
Meera Gandhi : Colleagues
S.K.Srivatsa : Colleagues  
 
 
 
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