Computer Science and Engineering, MIT Art, Design and Technology University, Pune, India.
International Journal of Science and Research Archive, 2025, 17(02), 166-171
Article DOI: 10.30574/ijsra.2025.17.2.2951
Received on 23 September 2025; revised on 02 November 2025; accepted on 04 November 2025
This paper presents AppNoc, an intelligent, application-aware firewall system integrated with an AI-driven log analytics engine for proactive network protection. Traditional firewalls primarily operate at the system or network level and lack visibility into application-level traffic behavior. AppNoc addresses this limitation by identifying which applications are generating network requests and applying customized firewall rules per application. In addition, it collects real-time network logs and uses machine learning algorithms to detect anomalous or suspicious patterns. The proposed system consists of a lightweight client-side agent that monitors and enforces application-specific policies and a centralized dashboard server that provides rule management, log visualization, and AI-based anomaly detection. AppNoc aims to simplify network security management, improve visibility into application traffic, and enable early detection of abnormal behaviors in enterprise and educational environments.
Application-Aware Firewall; Log Analytics; Machine Learning; Anomaly Detection; Network Security; Appnoc
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Omkar Gade, Akshat Bhatt, Shreeja Gundlur, Vijaya S.Patil and Abhishek Wagavekar. App Noc: App-Aware Firewall with AI Log Analytics. International Journal of Science and Research Archive, 2025, 17(02), 166-171. Article DOI: https://doi.org/10.30574/ijsra.2025.17.2.2951.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0







