2.1 The Proposed Work
The objective of proposed research is to study and analyze the presence of suspicious network traffic behavior of every categorization attack instance along with normal network traffic pattern collected from modified KDDCUP99 intrusion dataset, as appeared in the form of modified dataset sizes deployed in experimental work. The methodology is enhanced with the hybrid approach, i.e. determining the evolutionary computation technique combine with supervised machine learning classifiers intent to optimize the parameters to obtain fittest solutions as well from the refined attributes. In this proposed methodology, a new meta-heuristics model known as ‘Grey Wolf Optimizer’ (developed by Mirjalili et.al., 2014) organizes to …show more content…
Grey Wolf categorizes with four varied hierarchical postures exists in the live pack. They are known to be alpha, beta, delta and omega. Alpha based grey wolves pretend to be a leader and decision maker, makes the other categorization of grey wolves to organize the discipline to find the location of prey. Beta categorization grey wolves subordinate alpha based category with an intent to help the alpha in decision making. Beta categorization seems to be the best option in case of alpha situation known to be uncertainty. The remaining categories are known to be delta and omega. Delta based categorization seems to be a better option to subordinate the alpha and beta wolves, but the delta grey wolves dominate omega wolves. The social behavior of grey wolves seems to be making decisions in searching, tracking and attacking the prey. Based on this hierarchical behavior, the Grey Wolf Optimizer algorithm has been developed in terms of inhabitants based meta-heuristics algorithm simulates the leadership hierarchy and haunting mechanism of grey wolves in nature. Grey Wolf Optimizer built with two variant process to execute the work. They are known to be exploitation [attacking prey] and exploration [searching for prey]. The exploration process is being applied during haunting according to the position, do deviate it …show more content…
Therefore herewith, alpha; beta;delta assigned to be first three best solutions assigned to best optima about the potential location of prey. The remaining categorize i.e., omega makes them to follow and update their positions according to the positions of first three fittest search agents.
The statistical expression of the Grey Wolves encircling behavior is presented
The objective of proposed research is to study and analyze the presence of suspicious network traffic behavior of every categorization attack instance along with normal network traffic pattern collected from modified KDDCUP99 intrusion dataset, as appeared in the form of modified dataset sizes deployed in experimental work. The methodology is enhanced with the hybrid approach, i.e. determining the evolutionary computation technique combine with supervised machine learning classifiers intent to optimize the parameters to obtain fittest solutions as well from the refined attributes. In this proposed methodology, a new meta-heuristics model known as ‘Grey Wolf Optimizer’ (developed by Mirjalili et.al., 2014) organizes to …show more content…
Grey Wolf categorizes with four varied hierarchical postures exists in the live pack. They are known to be alpha, beta, delta and omega. Alpha based grey wolves pretend to be a leader and decision maker, makes the other categorization of grey wolves to organize the discipline to find the location of prey. Beta categorization grey wolves subordinate alpha based category with an intent to help the alpha in decision making. Beta categorization seems to be the best option in case of alpha situation known to be uncertainty. The remaining categories are known to be delta and omega. Delta based categorization seems to be a better option to subordinate the alpha and beta wolves, but the delta grey wolves dominate omega wolves. The social behavior of grey wolves seems to be making decisions in searching, tracking and attacking the prey. Based on this hierarchical behavior, the Grey Wolf Optimizer algorithm has been developed in terms of inhabitants based meta-heuristics algorithm simulates the leadership hierarchy and haunting mechanism of grey wolves in nature. Grey Wolf Optimizer built with two variant process to execute the work. They are known to be exploitation [attacking prey] and exploration [searching for prey]. The exploration process is being applied during haunting according to the position, do deviate it …show more content…
Therefore herewith, alpha; beta;delta assigned to be first three best solutions assigned to best optima about the potential location of prey. The remaining categorize i.e., omega makes them to follow and update their positions according to the positions of first three fittest search agents.
The statistical expression of the Grey Wolves encircling behavior is presented