• Dr. G. Yedukondalu
• Prof. M. Srinivasa Rao
• Prof. J. Anand Chandulal

Traffic classification is broadly utilized in different organization works, for example, programming designed systems administration and organization interruption location frameworks. Numerous traffic classification strategies have been proposed for grouping scrambled traffic by using a profound learning model without examining the bundle payload. Notwithstanding, they have a significant test in that the component of profound learning is mysterious. A glitch of the profound learning model might happen if the preparation dataset incorporates pernicious or mistaken information. Explainable artificial knowledge (XAI) can give some understanding for further developing the profound learning model by making sense of the reason for the glitch. In this paper, we propose a technique for making sense of the working component of profound learning-based traffic classification as a strategy for XAI in view of a hereditary calculation. We portray the instrument of the profound learning-based traffic classifier by measuring the significance of each element. Furthermore, we influence the hereditary calculation to create an element choice cover that chooses significant elements in the whole list of capabilities. To exhibit the proposed clarification technique, we executed a profound learning-based traffic classifier with an exactness of roughly 98.15%. In expansion, we present the significance of each element got from the proposed clarification strategy by defining the predominance rate.

Deep learning, AI, genetic algorithm, classification, network traffic.

"Implementation of Deep Learning Based Traffic Classification Model Using Genetic Artificial Intelligence Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.126-135, March-2021, Available :http://www.jetir.org/papers/JETIR2103407.pdf

"Implementation of Deep Learning Based Traffic Classification Model Using Genetic Artificial Intelligence Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp126-135, March-2021, Available at : http://www.jetir.org/papers/JETIR2103407.pdf