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Cybersecurity threats are rising in frequency and sophistication, which calls for the enhancement of better, real-time threat detection systems. This paper introduces a cyber threat intelligence (CTI) platform that combines a deep learning-based detection model with real-time log analysis with the utilization of security information and event management (SIEM) systems. A deep neural network trained with stochastic gradient descent (SGD) is at the heart of the proposed gadget, which uses log data to detect malicious activity. Logs are collected and consumed from the Wazuh platform, permitting real-time correlation and possibility tracking. A tailored dashboard presents a friendly interface for visualizing alerts and designs. The suggested structure mixes detection precision, machine scalability, and functioning responsiveness in changing network environments. Experimental outcomes demonstrate that the model is highly accurate and responsive in determining dangers, structuring its feasibility for real-time business environments.
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Copyright © 2025, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: R Obulakonda Reddy, r.obulakondareddy@iare.ac.in
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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