Network Traffic Classification Using Explainable Artificial Intelligence

1. M. Lopez-Martin, B. Carro, A. Sanchez-Esguevillas, and J. Lloret, ‘‘Network traffic classifier with convolutional and recurrent neural
networks for Internet of Things,’’ IEEE Access, vol. 5, pp. 18042–18050, 2017.
2. G. Aceto, D. Ciuonzo, A. Montieri, and A. Pescape, ‘‘Mobile encrypted traffic classification using deep learning: Experimental
evaluation, lessons learned, and challenges,’’ IEEE Trans. Netw. Service Manage., vol. 16, no. 2, pp. 445–458, Jun. 2019.
3. Ravindra Changala, "Sentiment Analysis in Social Media Using Deep Learning Techniques", International Journal of Intelligent Systems
and Applications in Engineering, 2024, 12(3), 1588–1597.
4. Ravindra Changala, "UI/UX Design for Online Learning Approach by Predictive Student Experience", 7th International Conference on
Electronics, Communication and Aerospace Technology, ICECA 2023 - Proceedings, 2023, pp. 794–799, IEEE Xplore.
5. Ravindra Changala, Framework for Virtualized Network Functions (VNFs) in Cloud of Things Based on Network Traffic Services,
International Journal on Recent and Innovation Trends in Computing and Communication, ISSN: 2321-8169 Volume 11, Issue 11s,
August 2023.
6. Montieri, D. Ciuonzo, G. Bovenzi, V. Persico, and A. Pescape, ‘‘A dive into the dark Web: Hierarchical traffic classification of anonymity
tools,’’ IEEE Trans. Netw. Sci. Eng., vol. 7, no. 3, pp. 1043–1054, Jul. 2020.
7. L. Grimaudo, M. Mellia, and E. Baralis, ‘‘Hierarchical learning for fine grained Internet traffic classification,’’ in Proc. 8th Int. Wireless
Commun. Mobile Comput. Conf. (IWCMC), Aug. 2012, pp. 463–468.
8. Ravindra Changala, Block Chain and Machine Learning Models to Evaluate Faults in the Smart Manufacturing System, International
Journal of Scientific Research in Science and Technology, Volume 10, Issue 5, ISSN: 2395-6011, Page Number 247-255, SeptemberOctober-2023.
9. Ravindra Changala, A Dominant Feature Selection Method for Deep Learning Based Traffic Classification Using a Genetic Algorithm,
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, ISSN : 2456-3307, Volume
8, Issue 6, November-December-2022, Page Number : 173-181.
10. Ravindra Changala, AIML and Remote Sensing System Developing the Marketing Strategy of Organic Food by Choosing Healthy Food,
International Journal of Scientific Research in Engineering and Management (IJSREM), Volume 07 Issue 09, ISSN: 2582-3930,
September 2023.
11. R. C. Fong and A. Vedaldi, ‘‘Interpretable explanations of black boxes by meaningful perturbation,’’ in Proc. IEEE Int. Conf. Comput.
Vis. (ICCV),Oct. 2017, pp. 3429–3437.
12. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhudinov, R. Zemel,and Y. Bengio, ‘‘Show, attend and tell: Neural image caption
generation with visual attention,’’ in Proc. Int. Conf. Mach. Learn., 2015,pp. 2048–2057.
13. K. He, X. Zhang, S. Ren, and J. Sun, ‘‘Deep residual learning for image recognition,’’ in Proc. IEEE Conf. Comput. Vis. Patt ern Recognit.
(CVPR), Jun. 2016, pp. 770–778.
14. Ravindra Changala, MapReduce Framework to Improve the Efficiency of Large Scale Item Sets in IoT Using Parallel Mining of
Representative Patterns in Big Data, International Journal of Scientific Research in Science and Technology, ISSN: 2395-6011, Volume
9, Issue 6, Page Number: 151-161, November 2022.
15. Ravindra Changala, A Novel Approach for Network Traffic and Attacks Analysis Using Big Data in Cloud Environment, International
Journal of Innovative Research in Computer and Communication Engineering: 2320-9798, Volume 10, Issue 11, November 2022.
16. M. Karakus and A. Durresi, ‘‘Quality of service (QoS) in software defined networking (SDN): A survey,’’ J. Netw. Comput. Appl., vol.
80, pp. 200–218, Feb. 2017.
17. Adadi and M. Berrada, ‘‘Peeking inside the black-box: A survey on explainable artificial intelligence (XAI),’’ IEEE Access, vol. 6, pp.
52138–52160, 2018.