Federated Learning for Dynamic Response to low-rate DDOS Attacks in (SDNs)
$750-1500 USD
Paid on delivery
- I am seeking a professional to design and implement a federated learning system for dynamic response to low-rate DDoS attacks in distributed Software-Defined Networks (Federated Learning for Dynamic Response to low-rate DDoS Attacks in SDNs).
- The goal of this system is to create a more secure and resilient network infrastructure by integrating the strengths of federated learning and deep reinforcement learning.
- The primary objective is to effectively mitigate various types of cyberattacks, demonstrating improved performance in attack detection and response time compared to traditional methods.
The system utilizes a Deep Q-Network (DQN) to learn optimal defense strategies against cyber-attacks. The federated learning component enables multiple SDN controllers to collaboratively train the DQN model without sharing raw data, thereby preserving data privacy. This approach aims to enhance the robustness and adaptability of the network's defense mechanisms, allowing for real-time, intelligent responses to cyber threats while maintaining a decentralized structure.
Project ID: #38901924
About the project
18 freelancers are bidding on average $1431 for this job
Hello Aso, I understand that you're looking for someone to develop a federated learning system aimed at improving the defense against low-rate DDoS attacks in Software-Defined Networks. My approach will involve combin More
I appreciate the opportunity to pitch for this crucial project. My name is Rashid and atop my extensive 5-year experience as a full-stack developer, I am skilled in numerous areas highly relevant to your project - part More
Hello Brother i am computer engineer and i have master degree in cryptography so may i can help you , thanks,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
