CyberVein’s vast data processing potential makes way for smarter cities and governments
In times when data is being created at a rapid pace, user privacy has become a myth. With social apps trying to collect users’ private information, it gets difficult to prevent the leakage of information. Enter CyberVein.
Adhering to an open, shared, and co-constructed attitude, CyberVein is a network of immutable, blockchain-based databases on which information can be securely processed, traded, and shared.
- Strong scalability and unlimited expansion
- Difficult to do malicious actions.
- It is safe and reliable.
- The partial consensus is more efficient
- Reduce fees and transaction costs
- CyberVein Consensus Layer – Data is more secure and the network is more independent.
The underlying potential of CyberVein can be realized anywhere vast amounts of data need to be processed immutably by several parties in parallel. It allows competing entities such as pharma companies, big data providers, or machine learning researchers, to share datasets and to massively increase their efficiency while preserving their independent economic interests.
- Smart cities and smarter governments:
In the age of data-driven smart-governance, CyberVein’s transparent design allows safe collection and processing of vast amounts of sensor information, without central points of control or failure.
- Cross-industry research and development:
CyberVein introduces economic incentives for Universities and research facilities to maintain their heavy-duty datasets, and to make them publicly available for further research and development.
* Identity anonymity
* Data privacy protection
* Precise permission control
- Application diversification
* Has a complete set of functions and easy to use, fulfilling the requirements for business applications, which can promote the practice of application implementation.
* Supports flexible management functions for user accounts, and uses the model of “role and permission” to realize alliance chain participant management.
* Has relatively higher transaction throughput and low latency, and it can expand capacity in parallel and support massive service volumes.
* Optimizes transaction processing flow and communication flow to improve the node processing capacity.
* Implements a highly efficient consensus algorithm system with a plug-in design that supports optimized PBFT and RAFT consensus algorithms.
* Has parallel computing architecture, it can expand capacity in parallel to meet the needs of massive service volumes.
- Controllable Security (Security)
* Multi-layered, comprehensive security protection to meet the high-security standards.
* Strong encryption protection for the communication layer, user data, and other modules.
* Supports multiple cryptographic algorithms, including the privacy protection algorithms based on cryptography.
* Provides the best practices for security, to ensure the security for the entire network.
A look at the underlying technology that fuels these use-cases
DAG, or Directed Acyclic Graph Ledgers, verify each other’s transaction on a P2P basis. CyberVein improves on DAG technology, and introduces a novel resource-conserving consensus mechanism, modifies the Solidity contracting language to adapt it for the processing and monetization of vast amounts of data.
CyberVein also allows maintaining databases on the blockchain itself. This means that all database operations, such as the manipulation of data fields, rows, and columns, are mediated via blockchain transactions. For this to work properly, CyberVein adds data-processing specific functions to the Solidity contracting language, including functions designed to directly monetize data stored on CyberVein databases.
The use of data: federal learning
In the attempt to solve the problem of data exchange of big data, traditional methods have already reached the bottleneck, CyberVein proposes a decentralized federated learning algorithm that uses knowledge distillation and other means to transfer knowledge from heterogeneous models and make full use of knowledge from different model structures. In federal learning,
- Each participant runs a DAI client locally, and each client is a blockchain node that participates in federated learning in a decentralized manner.
- Complete the construction of the CyberVein private chain cluster and distributed storage cluster. The communication generated by the platform passes through CyberVein, ensuring that all information in the entire system can be traced and valued.
- Integration of federated learning algorithms (traditional federated learning algorithms and new federated learning algorithms)
Proof of Contribution (PoC):
Proof of Contribution – CyberVein’s core value is that the contribution of storage space and bandwidth on the nodes is provided to the entire network, generating the rewards -CyberVein Tokens[CVT]- received by the nodes. Although this consensus mechanism is not a new concept, it is preferred over PoW, due to the excessive energy consumption of POW mining. CyberVein protects user privacy and data security by building a machine learning big data analysis and model for the third parties which will have broad application prospects in the sales, finance and supply chain industries.
CyberVein Token (CVT)
- Storage space contribution reward: In the CyberVein Proof of Contribution (PoC) consensus mechanism, data is distributedly stored in the storage space of contributors. The exchange efficiency of the data stream is based on the bandwidth of the storage space contributors.
- Storage payment: The data holder pays the corresponding storage fee based on the file size.
- Data interaction: In CyberVein’s federal learning platform, the data acquirer trades data with the data owner at an agreed price between the two parties for data modeling applications.
- GPU contribution and usage: Contributors and users agree on a price for the amount of GPU to be used for computing power.
CyberVein Trinity application scenarios
- Supply chain financial service platform
The underlying technology of the CyberVein platform can help develop a supply chain financial service platform to optimize the receivables financing process. By using blockchain technology, the platform links supply chain transaction information and
transfers credits from central enterprises to the suppliers to improve the allocation efficiency of financial resources among enterprises in the supply chain.
- Medical Research Platform
From the perspective of the medical big data platform value chain, the medical big data platform covers the entire process of the data value chain from data sources, data processing, data analysis to data applications, and realizes benefits from data storage,
data analysis, and data exchange transactions.
The big data platform supports the whole process of the clinical research procedures(discovery of scientific research inspiration, preliminary investigation, and verification, scientific research project establishment, determination of target population, the establishment of observation indicators, method of data collection, final statistical analysis and article writing, etc.), helping researchers with their scientific researches.
- Exploration and Discovery of Scientific Research Ideas
Throughout the scientific research process, for doctors, the exploration of scientific research ideas and the discovery of scientific research scenarios are the first keys to scientific research. Researchers can also achieve a new scientific research model through data discovery along with supervised and unsupervised machine learning, helping them to complete the first step of scientific research more easily and efficiently.
- Disease Map
The main purpose of constructing a disease map is to help doctors or researchers to better discover clinical and scientific value from the previous real medical record data through big data discovery and data visualization technology. With this, more disease
indicators can be discovered based on smarter algorithms, and the intelligent correlation analysis of related indicator data can be used to automatically realize the value of clinical data.
- Researching trends
The research trends based on big data can help users to understand the popular research trends and the situation of development in the corresponding professional fields, providing ideas for scientific research and facilitating doctors to quickly and accurately find starting points for scientific research.
- Scientific research analysis based on the time model
The big data application platform can build a time series model based on the patient’s key events, relying on the model to perform the intermediate process in the data processing while also eliminating factors such as a human error in the traditional data
- Specialized Disease Database
The medical records of patients are not stored in an organized manner in many hospitals, across the world at the moment. And with the onset of the COVID-19 pandemic, structured information of patients becomes more important than ever. CyberVein’s technology helps in organizing the data, for special disease researches, from the scientific research design stage, the data collection stage, to the continuation of historical scientific research results and the cross-department and cross-hospital researches among many other things. Thus the specialized disease database powered by CyberVein is indeed a reliable solution.
- Project Highlights
CyberVein has implemented practical applications such as “joint loan reserve management and reconciliation”, “supply chain financial services”, and “equity registration and services” to obtain results from commercial practices in the financial
CyberVein with its open, shared, and co-constructed attitude takes blockchain technology as the core to integrate data in various. CyberVein can be reached out at various social platforms like Facebook, Twitter, LinkedIn, Telegram, Instagram, YouTube, Reddit, and Bitcointalk. CVT is listed on Bittrex Global, OKEx, HitBTC, ZG-Top and Bit-Z.
Disclaimer: This a paid post, and should not be treated as news/advice.