RNN Based Cognitive Approach for Identifying End to End Malicious Event Using Static Election Algorithm

Abstract

Intelligence is the key characteristic to grasp environment and studies the same to give
flawless output for any kind of process. It has effective analyzing nature autonomously to
achieve a static or dynamic task on its personal talent .Cognitive intelligence are extremely
related to Artificial Intelligence which can competent to categorize any abnormalities,
investigation on sentiment, appraise images etc. Dynamic Recurrent Neural Network
(DRNN) is proposed to outperform testing subsequent to elimination of blare and weight
reckoning to act upon malicious event recognition task in network set of connections.
Dynamic array is used in the direction of accept surge stream of inward packets at router end
to keep away from fixed storage issues. The stored data in Dynamic array are taken and it is
allowed to undergo cleaning process, extraction process to find misconduct data along with
the help of RNN and Static Election algorithm.