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Introduction To Intrusion Detection System: Review
[Full Text]
AUTHOR(S)
Rajni Tewatia, Asha Mishra
KEYWORDS
Index Terms: Intrusion Detection system (IDS), Attack, Data, False alarm, Intruder, Network, Approach.
ABSTRACT
Abstract: Security of a network is always an important issue. With the continuously growing network, the basic security such as firewall, virus scanner is easily deceived by modern attackers who are experts in using software vulnerabilities to achieve their goals. For preventing such attacks, we need even smarter security mechanism which act proactively and intelligently. Intrusion Detection System is the solution of such requirement. Many techniques have been used to implement IDS. These technique basically used in the detector part of IDS such as Neural Network, Clustering, Pattern Matching, Rule Based, Fuzzy Logic, Genetic Algorithms and many more. To improve the performance of an IDS these approaches may be used in combination to build a hybrid IDS so that benefits of two o more approaches may be combined.
REFERENCES
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[5] Amit Kumar,Harish Chandra Maurya and Rahul Mishra “ A Research Paper on Hybrid Intrusion Detection System”, International Journal and Advanced Technology(IJEAT) ISSN:2249-8958, Volume-2, Issue-4, April 2013
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[7] Sharddha Surna “Intrusion Detection using Fuzzy Clustering and Artificial Neural Network”, Advances in Neural Networks, Fuzzy Systems and Artificial Intelligence.
[8] Mostaque Md. Morshedur Hassan “Network Intrusion Detection System Using Genetic Algorithm and Fuzzy Logic” International Journal of Innovative Research in Computer and Communication Engineering Vol. 1, Issue 7, September 2013.
[9] Alan Bivens, Chandrika Palagiri, Rasheda Smith, Boleslawszymanski, Mark Embrechts “Network-Based Intrusion Detection Using Neural Networks” Proc. Intelligent Engineering Systems through Artificial Neural Networks ANNIE-2002, St. Louis, MO, vol. 12, ASME Press, New York, NY, 2002, pp. 579-584.
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