International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Analysis of Network Traffic Using Deep Learning

V. Lakshmi ChaitanyaAssistant Professor, Department of Computer Science & Engineering, Santhiram Engineering College, IndiaK. VyshnaviStudent, Department of Computer Science &Engineering, Santhiram Engineering College, IndiaU. DeepikaStudent, Department of Computer Science &Engineering, Santhiram Engineering College, IndiaS. Sana SameerenStudent, Department of Computer Science &Engineering, Santhiram Engineering College, IndiaS. Misba SaniaStudent, Department of Computer Science &Engineering, Santhiram Engineering College, IndiaU. JayanthiStudent, Department of Computer Science &Engineering, Santhiram Engineering College, IndiaT. Shobha RaniStudent, Department of Computer Science &Engineering, Santhiram Engineering College, India

Vol 9 No 25 (2025): Volume 9, Special Issue of INSPIRE’25 April 2025 | Pages: 172-175

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 24-04-2025

doi Logo doi.org/10.47001/IRJIET/2025.INSPIRE28

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Abstract

Data protection, faster internet, and the detection of anomalous activity all depend on network traffic analysis. Large volumes of data cannot be processed using traditional ways as more gadgets connect to the internet.This study analyzes network traffic effectively using deep learning and big data. Deep learning models such as CNNS (Folding Networks) and RNN (Recursive Neural Networks) can help identify threats to identify traffic classification and abnormal patterns. Big data technologies such as Apache Spark and Hadoop process large amounts of data at lightning speeds. Together, these technologies can improve security, avoid cyberattacks, and accelerate and stabilize your network. This study explains how AI-based solutions can revolutionize network security. Issues, improvements and future developments in this area will also be resolved. The goal is to develop a more intelligent and secure network that protects data and improves internet performance.

Keywords

Big Data, Deep Learning, Network Traffic, Apache Hadoop


Citation of this Article

V. Lakshmi Chaitanya, K. Vyshnavi, U. Deepika, S. Sana Sameeren, S. Misba Sania, U. Jayanthi, & T. Shobha Rani. (2025). Analysis of Network Traffic Using Deep Learning. In proceeding of International Conference on Sustainable Practices and Innovations in Research and Engineering (INSPIRE'25), published by IRJIET, Volume 9, Special Issue of INSPIRE’25, pp 172-175. Article DOI https://doi.org/10.47001/IRJIET/2025.INSPIRE28

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