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IJSTR >> Volume 8 - Issue 11, November 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Intrusion Detection Using Negative Selection Based Neural Network Algorithm

[Full Text]

 

AUTHOR(S)

Divya Sharma, Sarita Singh Bhadauria

 

KEYWORDS

Intrusion, Intrusion detection, Negative selection, Data processing, KDD cup dataset, Artificial neural network, Cyber security.

 

ABSTRACT

Intrusion is the biggest problem in the world of digitalization. Everything is inter connected with each other makes it easier to use even for intruders. Intrusion detection system helps in detecting security breaches, so it can be prevented /handled. In this paper, a hybrid approach i.e. negative selection based neural network (NS-ANN) approach is presented. The proposed algorithm is implemented using Java over KDD cup dataset. The result computation obtained using confusion matrix and computation parameters. The performance is compared to existing techniques and it is seen the efficiency of proposed work is better over other traditional available solutions.Intrusion is the biggest problem in the world of digitalization. Everything is inter connected with each other makes it easier to use even for intruders. Intrusion detection system helps in detecting security breaches, so it can be prevented /handled. In this paper, a hybrid approach i.e. negative selection based neural network (NS-ANN) approach is presented. The proposed algorithm is implemented using Java over KDD cup dataset. The result computation obtained using confusion matrix and computation parameters. The performance is compared to existing techniques and it is seen the efficiency of proposed work is better over other traditional available solutions.

 

REFERENCES

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