Multi-classification approach for detecting network attacks

2013 IEEE Conference on Information and Communication Technologies, ICT 2013

Volumn , Issue , 2013, Pages 1114-1117

  Kumaravel, A ^a   Niraisha, M ^a  

^a BHARATH UNIVERSITY   (India)

Author keywords

Classification; DataMining; Intrusion detection system; Layered approach; Network Security

Indexed keywords

CLASSIFICATION RATES; COMPUTER AND NETWORKS; INTRUSION DETECTION SYSTEMS; LAYERED APPROACHES; MULTI-CLASSIFICATION; NETWORK ENVIRONMENTS; NUMBER OF FALSE ALARMS; SECURITY RISKS;

CLASSIFICATION (OF INFORMATION); COMPUTER NETWORKS; DATA MINING; INFORMATION TECHNOLOGY; INTRUSION DETECTION; NETWORK SECURITY;

COMPUTER CRIME;

EID: 84881642295     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CICT.2013.6558266     Document Type: Conference Paper

References (6)

1. OludeleAwodele, Sunday Idowu, OmotolaAnjorin, andVincent J. Joshua, "A Multi-Layered Approach to the Design of Intelligent Intrusion Detection and Prevention System(IIDPS)," Issues in Informing Science and InformationTechnology Volume 6, 2009.
2. Neelam Sharma, Saurabh Mukherjee, "Layered Approach for Intrusion Detection Using NaïveBayes Classifier," ICACCI'12, August 3-5, 2012, Chennai, T Nadu, India.
3. P. GiftyJeya, M.Ravichandran, C.S. Ravichandran, "Efficient Classifier for R2L and U2R Attacks," International Journal of Computer Applications (0975 -8887)Volume 45- No.21, May 2012.
4. Ankita Gaur, VineetRichariya, "A Layered Approach for Intrusion DetectionUsing Meta-modeling with ClassificationTechniques," International Journal of Computer Technology and Electronics Engineering (IJCTEE) Volume 1, Issue 2.
5. Weka:http://www.cs.waikato.ac.nz/~ml/weka/
6. "NSL-KDD dataset for network -based intrusion detectionsystems" available on http://iscx.info/NSL-KDD/