- Torna al menu
- Torna al menuPrezzi
- Torna al menuRicerca
- Torna al menu
- Torna al menu
- Torna al menu
- Torna al menu
- Torna al menuWebinar ed Eventi
Vana
Vana Price Converter
Vana Information
Vana Supported Platforms
| VANA | ERC20 | ETH | 0x7ff7fa94b8b66ef313f7970d4eebd2cb3103a2c0 | 2024-11-24 |
| VANA | ERC20 | BASE | 0x7ff7fa94b8b66ef313f7970d4eebd2cb3103a2c0 | 2024-11-24 |
| VANA | ERC20 | ARB | 0x7ff7fa94b8b66ef313f7970d4eebd2cb3103a2c0 | 2024-11-24 |
| VANA | BEP20 | BNB | 0x7ff7fa94b8b66ef313f7970d4eebd2cb3103a2c0 | 2024-11-24 |
| VANA | ERC20 | OP | 0x7ff7fa94b8b66ef313f7970d4eebd2cb3103a2c0 | 2024-11-24 |
About Vana
Vana is a decentralised protocol designed to give individuals complete ownership, control, and monetisation of their personal data. Built on an EVM-compatible layer-1 blockchain, it introduces Data Liquidity Pools (DLPs), which serve as decentralised marketplaces where users can contribute, validate, and tokenise their data into valuable assets. By combining blockchain technology, privacy-preserving cryptography, and tokenised incentives, Vana transforms personal data into a user-owned resource while maintaining privacy and security.
Vana addresses the imbalance in the current data economy, where centralised platforms profit disproportionately from user-generated data. The protocol empowers users to decide how their data is used, while ensuring they receive fair rewards for its contributions. This innovative system enables applications such as AI model training, decentralised applications (dApps), and advanced data-driven solutions.
Data Monetisation and Governance
- Users contribute their data to DLPs, where it is securely validated, tokenised, and monetised. Contributors earn $VANA tokens or DLP-specific tokens as rewards, reflecting the quality and utility of their data. These tokens also grant governance rights, allowing participants to influence decisions about data use, reward distribution, and network operations through decentralised autonomous organisations (DataDAOs).
AI Model Development
- Aggregated datasets in DLPs enable the training of decentralised AI models while preserving individual privacy. These models can be used for applications like language processing, sentiment analysis, healthcare solutions, and other domain-specific AI services. Contributors benefit financially from their data’s role in these innovations.
Privacy and Security
- Vana ensures data privacy through advanced technologies like Trusted Execution Environments (TEEs) and Zero-Knowledge Proofs (ZKPs). These methods allow for secure data validation and usage without exposing raw data. This makes Vana suitable for industries with strict privacy requirements, such as healthcare and finance.
Interoperability Across Ecosystems
- The Vana protocol supports cross-chain functionality, integrating seamlessly with blockchains like Ethereum, Binance Smart Chain, and Polygon. This interoperability enables users and developers to access and utilise Vana’s ecosystem across decentralised platforms.
Financial Products and Data Trading
- The tokenisation of data enables various financial applications, including:
- Data Trading Markets: Tokenised datasets can be bought and sold on decentralised exchanges.
- Data Derivatives: Futures, options, and other instruments tied to data pools or AI models.
- Data Yield Farming and Lending: Users can stake or lend their data-backed tokens for additional rewards, creating new opportunities in decentralised finance (DeFi).
- The tokenisation of data enables various financial applications, including:
Vana employs a robust framework to ensure the quality and security of data contributions while safeguarding user privacy. Data validation and blockchain security are handled through distinct systems that operate in complementary ways:
- Proof of Stake (PoS): The blockchain uses PoS as its consensus mechanism, securing the network and validating transactions.
- Proof of Contribution (PoC): PoC operates at the data level, validating user-submitted data contributions within Data Liquidity Pools (DLPs).
Key elements of Vana’s security and data quality framework include:
Trusted Execution Environments (TEEs):
Data is validated within secure enclaves, ensuring that sensitive information remains private and inaccessible to unauthorised parties. These environments enable computations on data while keeping it encrypted.Zero-Knowledge Proofs (ZKPs):
Contributors can prove their data meets the required criteria without exposing its contents. This ensures privacy during validation while maintaining data integrity.Customised Validation Criteria:
Each Data Liquidity Pool (DLP) defines unique rules for data validation, tailored to its specific purpose. Examples include:- Health data pools prioritising accuracy and recency.
- Social media data pools focusing on engagement metrics.
Data Ownership and Governance:
Once validated, contributors retain ownership of their data and participate in governance decisions within their respective DataDAOs. This allows them to influence how their data is used and managed within the ecosystem.
This framework is designed to combine blockchain transparency with privacy-preserving technologies, enabling the validation and use of high-quality data while maintaining user control. These measures support the creation of datasets for applications such as AI model training and decentralised analytics while addressing privacy and ethical concerns.