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My goal is to prove that 50 completely separate Indian embassies can collaboratively train a powerful intrusion-detection model without ever sharing raw traffic logs. Each embassy keeps its packets local, trains an IDS in Python, then ships only the updated weights to a permissioned blockchain that averages them and sends back the enhanced parameters. Key points I need turned into code: • Dual-framework training loops: the local agent must be able to switch between PyTorch and TensorFlow so each site runs whichever stack its engineers prefer. • Attack coverage baked into the dataset pipeline: the IDS must correctly classify Malware, Phishing, and DDoS patterns. Synthetic generation for edge cases is fine as long as the final validation shows clear detection rates for all three. • Smart-contract aggregator: the chain’s sole responsibility is aggregating model weights. I want a concise contract—Solidity for an Ethereum PoA test-network or chaincode for Hyperledger Fabric—that stores submissions, computes the federated average, and emits the new global state. No on-chain data other than floats and a small hash for versioning. • [login to view URL] bridge: a lightweight Python client that listens for the latest global weights, injects them back into the local model, and kicks off the next training epoch. Acceptance will be based on: 1. A demo with three simulated embassies showing local training, on-chain aggregation, and convergence after several rounds. 2. Reproducible scripts (Docker or Compose welcome) so I can spin up nodes and repeat the run on my machine. 3. A short README explaining how to switch between PyTorch and TensorFlow and how to extend the attack library with new classes. If you already have experience with federated learning, Hyperledger Fabric, Solidity, or [login to view URL] integrations, the finish line should be straightforward. I’m happy to iterate on architecture decisions, but the delivered code needs to compile, deploy, and hit the accuracy targets out of the box.
Project ID: 40201629
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Active 11 days ago
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5 freelancers are bidding on average ₹9,903 INR for this job

Hello , I checked your project, and it looks interesting. This is something we already work on, so the requirements are clear from the start. We mainly work on Java, Python, Linux, Ubuntu, Blockchain, Solidity, Smart Contracts, Hyperledger Fabric We focus on making things simple, reliable, and actually useful in real life not overcomplicated stuff. Let’s connect in chat and see if we’re a good fit for this. Best Regards, Ali nawaz
₹25,000 INR in 8 days
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Hello Mate!Greetings , Good afternoon! I am skilled mobile coder with skills including Blockchain, Ubuntu, Python, Hyperledger Fabric, Smart Contracts, Solidity, Java and Linux. Please contact me to discuss more regarding this project. Thank you for your attention
₹4,513 INR in 4 days
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As a seasoned Data Scientist with profound expertise in Blockchain integration, I am confident that I am the best professional to carry out your project. Having explored various aspects of data-driven technologies including Sentiment Analytics, Neural Machine Translation and the likes, I fully grasp the potentials and capabilities of federated learning and blockchain based IDS. I have also had the privilege of putting these skills into use in a number of real-world settings and open-source projects. Key to your project is the ability to fluidly switch between PyTorch and TensorFlow frameworks depending on engineers' preferences on each site. This is something I can assure you. Furthermore, my understanding of Natural Language Processing would come handy in incorporating attack coverage within your dataset pipeline to ensure that Malware, Phishing, and DDoS patterns are correctly classified through synthetic generation for edge cases. Given my capability in delivering high-standard code along with detailed documentation and scripts for reproducibility, your project will definitely be in the right hands if assigned to me.
₹7,000 INR in 7 days
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Bengaluru, India
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