Network Traffic Analysis In IOT Devices Using ELK Stack

The explosive growth of Internet of Things (IoT) devices has significantly reshaped today’s network environments, creating a surge in data and introducing new challenges in managing and securing network traffic. In response, this paper introduces a practical and adaptive framework tailored for analyzing IoT traffic using the ELK Stack—Elasticsearch, Logstash, and Kibana. Logstash is used to collect and transform data efficiently, Elasticsearch handles scalable storage and fast querying, and Kibana delivers easy-to-understand visualizations to track trends and detect unusual patterns.To boost the system's intelligence, machine learning is integrated into the framework, enabling it to spot anomalies and potential threats in real time. Testing in diverse IoT scenarios showed faster threat detection and improved accuracy in identifying unauthorized access, proving the framework’s flexibility and effectiveness across various devices and network conditions.With real-time insights into bandwidth consumption and device activity, network administrators can take proactive steps to manage threats and optimize performance. As IoT networks continue to grow in complexity, this research emphasizes the importance of smart, scalable analysis tools. Future development will focus on incorporating advanced predictive models to further enhance threat detection and support more resilient, secure IoT ecosystems.