🌐 A Scalable Framework for Real-Time Network Security Traffic Analysis and Attack Detection Using Machine & Deep Learning 🤖
In today’s hyper-connected cyber realm 🌍, massive volumes of network traffic surge every millisecond. Detecting malicious patterns amidst this data deluge demands real-time, intelligent frameworks . This study proposes a scalable, AI-powered infrastructure that autonomously monitors, analyzes, and detects security anomalies before they escalate into full-blown cyber threats 🚨. ⚙️ 2. Framework Architecture: Building the Digital Shield The proposed framework integrates distributed computing and automated intelligence pipelines to ensure speed, precision, and adaptability. 2.1 Data Ingestion Layer 🧩 – Continuously captures live traffic from diverse sources like IoT devices, cloud servers, and routers. 2.2 Preprocessing Engine 🧠 – Cleans, normalizes, and transforms raw packets into structured, feature-rich datasets. 2.3 Scalable Infrastructure ☁️ – Employs technologies such as Apache Kafka and Spark Streaming for real-time data handling and scalability. 🧬 3. I...