Ramen Protocol

A Protocol that allows people to preserve cultural assets or secret knowledge, pass them securely across generations, and visualize each inheritance so every contributor is recognized.

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Categories

  • Privacidad, Identidad y Datos
  • 💰Scroll - Prize $4000 - Best Crypto Consumer App
  • 💰Scroll - Prize $1000 - Deploy on Scroll
  • 💰Arkiv- Prize $3500 - Track Principal
  • 💰Arkiv- Prize $1500 - Micro Bounties

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Description

Ramen Protocol

A decentralized protocol for preserving and passing down cultural assets and secret knowledge across generations with privacy, verifiability, and traceability.

🎯 Overview

Ramen Protocol enables individuals to securely inherit sensitive knowledge to chosen successors while maintaining privacy through encryption and creating permanent, verifiable records of cultural lineage on-chain.

📺 Important Links

👥 Team

  • cruujon (Keita Kuroiwa) - @cruujon
  • Dario Macs - @DaroMacs
  • Ariel - @ariiellus

🔍 The Problem

Human knowledge and culture depend on inheritance—skills, wisdom, and traditions passed across generations. Yet today, there's no secure, privacy-preserving method to:

  1. Pass down sensitive knowledge to a chosen successor
  2. Make inheritance relationships visible and verifiable
  3. Create permanent, traceable records of cultural lineage

Core Issues

🔒 Invisible & Unverifiable Relationships

No reliable way exists to document who passed what to whom. Contributions go unrecognized, unrewarded, and untracked—making knowledge transmission structurally fragile.

⚖️ Privacy vs. Verifiability Trade-off

Current systems force users to choose between proving contribution, keeping content private, or ensuring censorship-resistance. True secret knowledge sharing requires compromising on at least one dimension.

🎯 Missing Incentives

When efforts leave no trace or recognition, motivation declines. Invisible transmission leads to disengagement, accelerating cultural loss.

🏛️ No Support for True Inheritors

Without verifiable lineage records, preservation organizations cannot identify, support, or fund the people truly maintaining cultural continuity. This leaves traditions vulnerable to distortion or erasure.

✨ The Solution

Ramen Protocol creates a privacy-preserving, verifiable inheritance system by combining:

  • On-chain lineage tracking: Records who (wallet address) passed knowledge to whom, creating immutable provenance
  • Client-side encryption: Files encrypted in-browser before upload using AES-256-GCM
  • Successor-only decryption: Only the designated successor's wallet can derive the decryption key
  • Decentralized storage: Encrypted data stored on IPFS; only the hash (CID) recorded on-chain
  • Fair revenue distribution: Visible inheritance chains enable proportional compensation based on contribution lineage

Target Users

  • Individuals wanting to pass down secret & valuable knowledge privately.
  • Examples:
    • A restaurant owner with a secret recipe but no successor.
    • Craftsmen with unique techniques that cannot be publicised.
    • Oral storytelling traditions and local cultural narratives.
    • A trader who has secret investment knowledge and a unique method

🎭 Target Users

Primary Use Cases

🍜 Restaurant Owners

Preserve secret recipes without public disclosure while ensuring they pass to the right successor.

🎨 Master Craftspeople

Document unique techniques that cannot be publicized but need preservation.

📖 Oral Tradition Keepers

Record storytelling traditions and local cultural narratives with verifiable lineage.

💼 Knowledge Professionals

Pass down proprietary methods, investment strategies, or specialized expertise privately.

🏗️ Architecture Overview

System Components

  • Frontend (Next.js + Wagmi + viem) Handles:

    • file encryption/decryption (Web Crypto API)
    • IPFS upload/download (via API route or direct)
    • contract calls
    • lineage display
  • Blockchain (Scroll Sepolia / Solidity) Responsible for:

    • storing inheritance metadata
    • verifying successor identity (msg.sender)
    • preserving lineage
  • Storage: IPFS + Arkiv

    • Store encrypted files (IPFS)
    • Handles merkleTree commitments
    • Manage IPFS file identification

Ramen Protocol Architecture:


Ramen Protocol

Core User Flow:

  1. User creates a new vault where stores in IPFS the information that want to preserve
  2. He passes a "secret" which can be a secret word, phrase, private/public key, or whatever
  3. The interaction is via our contract zkheriloom3, which uses a relayer to connect to Semaphore
  4. Through Semaphore we storage commitment hashes from users to preserve privacy via Incremental Merkle Trees
  5. All the merkleTreeData and IPFS CIDs are storage in Arkiv to maintain the correct record to reconstruct IMTs

Security Properties (MVP)

  • Files are encrypted before upload (E2E).
  • Only successor wallet can derive the correct key.
  • No keys stored on-chain, off-chain, or in ARKIV.
  • IPFS blobs are public but unreadable.
  • On-chain lineage is tamper-proof.

Security limitations

  • If successor wallet is compromised, the encrypted file can be decrypted.
  • No key rotation mechanism yet.
  • Browser-based crypto requires trustworthy hosting.

Tech Stack

  • Blockchain: Scroll Sepolia
  • Smart Contracts: Solidity + Foundry
  • Libraries: Semaphore SDK
  • Frontend: Next.js 14, TypeScript, Wagmi, viem, shadcn/ui
  • Storage: IPFS + Arkiv

Roadmap

Short Term

  • Deploy to mainnet

Medium Term

  • EAS integration

    • Integrate with EAS so other protocols/organizations can reuse inheritance lineage permissionlessly.

  • Marketplace function
    • To enable each inheritor to monetize through their secret knowledge, we integrate Market Marketplace feature where the successor can buy the knowledge from the inheritor. Once the knowledge is sold, the revenue will be automatically distributed according to the dependency of each inheritance.
  • Run Public Goods Funding rounds with Local Government/Organizations preserving cultural knowledge.  
    • Integrate the Gitcoin stack for donation and grant-based preservation funding.
    • Run funding rounds for cultural assets.
    • Collaborate with local governments and cultural institutions to test real-world deployments.
  • AI Integration

    • Automatically estimate cultural/economic importance scores for each inheritance.
    • Auto-tag inherited data for better discoverability.
    • Match inheritors and successors algorithmically

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