In the real world it is a routine that one must deal with uncertainty when security is concerned. Intrusion detection systems offer a new challenge in handling uncertainty due to imprecise knowledge in classifying the normal or abnormal behaviour patterns. In this paper we have introduced an emerging approach for intrusion detection system using Neutrosophic Logic Classifier which is an extension/combination of the fuzzy logic, intuitionistic logic, paraconsistent logic, and the three-valued logics that use an indeterminate value. It is capable of handling fuzzy, vague, incomplete and inconsistent information under one framework. Using this new approach there is an increase in detection rate and the significant decrease in false alarm rate. The proposed method tripartitions the dataset into normal, abnormal and indeterministic based on the degree of membership of truthness, degree of membership of indeterminacy and degree of membership of falsity. The proposed method was tested up on KDD Cup 99 dataset. The Neutrosophic Logic Classifier generates the Neutrosophic rules to determine the intrusion in progress. Improvised genetic algorithm is adopted in order to detect the potential rules for performing better classification. This paper exhibits the efficiency of handling uncertainty in Intrusion detection precisely using Neutrosophic Logic Classifier based Intrusion detection System.

One of the toughest challenges in Intrusion Detection System is uncertainty handling.  he normal and the abnormal behaviors in networked computers are hard to predict as the boundaries cannot be well defined. The prediction of the normal or abnormal behaviors is done by the comparison with predefined classes to find the most similar one. This prediction process may generate false alarms in many anomaly based intrusion detection systems. Consequently, we observed uncertainty where there is a fair chance of the existence of a non-null hesitation part at each moment of evaluation of an unknown object. A new technique is implemented in this paper using Intuitionistic fuzzy logic which is a generalization of fuzzy logic. In this model the false alarm rate in determining intrusive activities can be reduced. A set of Intuitionistic fuzzy rules can be used to define the normal, abnormal and indeterministic behavior in a computer network. An Intuitionistic fuzzy  inference algorithm can be applied over such rules to determine when an intrusion is in progress. The main problem with this approach is to generate good Intuitionistic fuzzy classifiers to detect intrusions. The rules generated by Intuitionistic fuzzy classifiers are fine tuned using improvised genetic algorithm that can detect anomalies and some specific intrusions. The main idea is to evolve three rules, one for the normal class, second for the abnormal class and third of indeterministic class using KDD Cup 99 Dataset. This paper exhibits the performance of Emergent Intuitionistic fuzzy classifiers in intrusion detection.

In general, some static analysis of the predictable flow of the compressible and caisson fluid of some infinite vertical plates is determined by taking into account its varying mass or constant fluid flow and the uniform increase of the partition temperature. Differential equations can be predicted using different components of the Laplace transformation technique. Usually, two different solutions are available when the fluid flows in a particular direction. In this paper, an improved method for calculating the velocity of different fluids is proposed. Its possibilities are designed to calculate the different types of events that take place near the high temperature plates of the liquid. The results are compared with the flow along the plates at a near constant temperature.

In general, some static analysis of the predictable flow of the compressible and caisson fluid of some infinite vertical plates is determined by taking into account its varying mass or constant fluid flow and the uniform increase of the partition temperature. Differential equations can be predicted using different components of the Laplace transformation technique. Usually, two different solutions are available when the fluid flows in a particular direction. In this paper, an improved method for calculating the velocity of different fluids is proposed. Its possibilities are designed to calculate the different types of events that take place near the high temperature plates of the liquid. The results are compared with the flow along the plates at a near constant temperature.

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