A Novel Intelligent Intrusion Detection, Decision, Response System.
IEICE Transactions 01/2006; 89-A:1630-1637. DOI:10.1093/ietfec/e89-a.6.1630
Conference Proceeding: A new genetic algorithm approach for intrusion response system in computer networks[show abstract] [hide abstract]
ABSTRACT: This paper deals with a combination of work in the fields of artificial intelligence and computer security. It describes a decision model based on a new genetic algorithm approach for intrusion response system (NGAA-IRS). A brief survey of intrusion detection and response system (IDRS), genetic algorithm (GA), and its application to IDRS are presented. Then, the proposed model, parameters and evolution process for GA are discussed in details. The model is characterized by a new implementation of individual structure based on a matrix of response-resource entries and a fitness function based on cost benefit approach for selecting the appropriate solution. These features are specific to NGAA-IRS model and do not be used in other implementations beforehand.Computers and Communications, 2009. ISCC 2009. IEEE Symposium on; 08/2009
Conference Proceeding: Application of Neuro-Fuzzy Approach for I2D2RS[show abstract] [hide abstract]
ABSTRACT: In this paper, one backpropagation neural network (BPNN) was utilized to classify the grades of periodicity of the time intervals that is one of the most important evidence of the intrusion decision in the intelligent intrusion detection, decision, response system (I<sup>2</sup>D<sup>2</sup>RS) for resolving its problems: multi-inputs/outputs, non-linearing and complexity. Neural network is good at processing these problems. And for the Neuro-Fuzzy approach was introduced in the I<sup>2</sup>D<sup>2</sup>RS the fuzzy rules was simplified and the system's processing speed was accelerated.Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on; 10/2007
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ABSTRACT: Neural networks have good learning and associative memory abilities have been widely applied to various fields. In this paper, we employed the Back propagation Neural Network (BPNN) to replace the fuzzy methods of the Intelligent Intrusion Detection, Decision, Response System (IIDDRS) to decide the intrusion. Through this improvement the processing of the system was simplified and the performance of the system was enhanced in the Intrusion Decision. The efficiency of these improvements was confirmed with the experiments.Intelligent Networks and Intelligent Systems, International Workshop on. 01/2008;
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