Deep Packet Inspection Using Deep Learning

Project Title

Deep Packet Inspection Using Deep Learning

Project Area of Specialization Artificial IntelligenceProject Summary

In current scenario, the world is connected by internet and we have High speed data packets transfer on network. A Ecommerce website to a File transfer system or a Social media application to an email Site. we have data packets transference in all applications connected to internet. Since world of internet is not secured considering there is a high possibility data packets can be changed to have Malicious Content.

In our research, we are developing a distributed  environment where at PC1 we will capture the incoming packets and parse it for extracting payload and forwarding to PC2 using RDMA over Infiniband to achieve high speed packet transference. At PC2 we classify payload images as benign or malicious on our trained CNN model over GPUS.

Project Objectives

To implement and improve Deep Packet Inspection (DPI) which can be integrated in Modern Network Traffic Classification Tools to Classify Data Packet.

Project Implementation Method

we are developing a distributed  environment where at PC1 we will capture the incoming packets and parse it for extracting payload and forwarding to PC2 using RDMA over Infiniband to achieve high speed packet transference. At PC2 we classify payload images as benign or malicious on our trained CNN model over GPUS.

Benefits of the Project

This system can be deployed at internet service provider (ISP) and is the future of smart cities.

Technical Details of Final Deliverable

We have trained CNN model on GPUS and our deliverable includes Research paper and complete integerated realtime deep packet inspection.

Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development GoalsRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	70000
Geforce Gtx 1080	Equipment	1	70000	70000