Computer Science and Engineering MIT Art, Design and Technology University Pune, India.
International Journal of Science and Research Archive, 2026, 19(02), 251-257
Article DOI: 10.30574/ijsra.2026.19.2.0996
Received on 27 March 2026; revised on 02 May 2026; accepted on 05 May 2026
This study introduces App Noc, an advanced firewall solution that is aware of application-level activity and enhanced with an AI-powered log analysis system for proactive security. Traditional firewall systems generally function at the network or system level and do not provide insights into how individual applications behave in terms of network usage. App Noc overcomes this challenge by detecting which applications are responsible for network communication and enforcing tailored security rules for each application. Furthermore, it gathers live network logs and applies machine learning techniques to identify unusual or potentially harmful patterns. The architecture includes a lightweight client-side agent responsible for monitoring and enforcing policies, along with a centralized dashboard server for managing rules, visualizing logs, and performing anomaly detection using AI. The objective of App Noc is to streamline network security operations, enhance visibility into application-driven traffic, and facilitate early identification of suspicious behavior in both enterprise and academic settings.
Application-Aware Firewall; Log Analytics; Machine Learning; Anomaly Detection; Network Security; App Noc
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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, 2026, 19(02), 251-257. Article DOI: https://doi.org/10.30574/ijsra.2026.19.2.0996.






