A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems.
Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks.
Centre for Information Super Highway (CISH), School of Computing, SASTRA University, Thanjavur- 613401, Tamil Nadu, India. Electronic address: gauthamaraman_mr@sastra.ac.in.
M R Gauthama
MRG
Raman
Centre for Information Super Highway (CISH), School of Computing, SASTRA University, Thanjavur- 613401, Tamil Nadu, India. Electronic address: nivethitha@sastra.ac.in.
Nivethitha
N
Somu
Discrete Mathematics Research Laboratory (DMRL), Department of Mathematics, SASTRA University, Thanjavur- 613401, Tamil Nadu, India. Electronic address: kannan@maths.sastra.edu.
Kannan
K
Kirthivasan
Centre for Information Super Highway (CISH), School of Computing, SASTRA University, Thanjavur- 613401, Tamil Nadu, India. Electronic address: sriram@it.sastra.edu.
V S Shankar
VSS
Sriram
D056667:Biometric Identification / Q000379:methods* / Q000592:standards; D016571:Neural Networks, Computer
Arithmetic Residue (AR); Artificial Neural Network (ANN); Feature selection and classification; Hypergraph (HG); Intrusion Detection Systems (IDSs); Probabilistic Neural Network (PNN)