In this internship, you will work collaboratively in a team of three interns to develop an intelligent network traffic monitoring and security analytics system that integrates real-time data collection, anomaly detection, and machine learning-based traffic characterization. This project will provide hands-on experience in systems programming, AI-driven cybersecurity, and 5G traffic analysis.

You will develop a series of Docker-containerized network services leveraging machine learning to achieve the following objectives:

1. Detect anomalies and potential security compromises in real time based on data collected by CloudLens vTAP Agents.
2. Feed an NVIDIA device with traffic data to obtain real-time traffic characterization, inferring whether an encrypted stream corresponds to a video call, audio call, or other types of traffic.
3. Suggest the best configuration for achieving different monitoring goals in 5G SBI deployments using CloudLens solutions.

What you will gain:

• AI/ML Expertise: Gain top-notch, practical AI/ML skills.
• Real-World Application: Work on network & packet inspection challenges.
• Team Collaboration: Experience dynamic teamwork and code collaboration.
• Cutting-Edge Tools: Engage with virtualization, DPI for TCP/UDP, high-performance packet processing, OVS, DPDK, and 5G SBI.