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A Hybrid Snort-Negative Selection Network Intrusion Detection Technique

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Tarek M. Mahmoud, Abdelmgeid A. Ali, Hussein M. Elshafie

Tarek M Mahmoud, Abdelmgeid A Ali and Hussein M Elshafie. A Hybrid Snort-Negative Selection Network Intrusion Detection Technique. International Journal of Computer Applications 146(5):24-31, July 2016. BibTeX

	author = {Tarek M. Mahmoud and Abdelmgeid A. Ali and Hussein M. Elshafie},
	title = {A Hybrid Snort-Negative Selection Network Intrusion Detection Technique},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2016},
	volume = {146},
	number = {5},
	month = {Jul},
	year = {2016},
	issn = {0975-8887},
	pages = {24-31},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2016910703},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Network Intrusion Detection Systems (NIDSs) are systems that monitor computer networks to detect, identify and prevent the malicious events, which attempt to compromise the integrity, confidentiality or availability of computer networks. The NIDS may be classified according to the detection technique into two types, the "Signature-Based" and "Anomaly-Based" NIDS. In order to increase the efficiency of the NIDS, a hybrid signature-anomaly NIDS based on both snort and negative selection algorithm is proposed. To evaluate the efficacy of the proposed system the 1999 DARPA data set is used. The experimental results show that the performance of the proposed system is more efficient than using snort on its own.


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Signature Based, Anomaly Based, Snort, Negative Selection