A blockchain-based access control for big data

Blockchain and Distributed Ledger Technology - enabled architectures for improving healthcare View all Articles. Blockchain solutions offer efficient approaches for trustworthy data management, especially in the medical field when storing and processing sensitive patient data. Many institutional and industrial facilities have already recognized the importance of the technology for the health sector and have also formulated basic ideas, concepts and main use cases, but concrete implementations and executions are comparatively rare. This mini review examines current research on specific blockchain implementations in healthcare that go beyond the state of concept studies or theoretical implementation ideas and describes the most promising systems based on systematic literature research. The review shows that secure storage and easy access to complete patient data is becoming increasingly important. Blockchain technology can be used as a secure, transparent and digital way to meet these needs.

We are searching data for your request:

Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

Content:

• Storage news ticker – 3 February 2022
• Blockchain-based access control management for Decentralized Online Social Networks
• Search Form
• A Blockchain-based Access Control for Big Data
• Blockchain-Based Privacy Protection Scheme for IoT-Assisted Educational Big Data Management
• Blockchain-Based Access Control and Data Sharing Mechanism in Cloud Decentralized Storage System
• Blockchain Explained

WATCH RELATED VIDEO: Temporal: Blockchain-based Security Framework for Cyber Physical Systems (BSF-CPS) - Dr. A. Vyas

Storage news ticker – 3 February 2022

Welcome to Finextra. We use cookies to help us to deliver our services. We'll assume you're ok with this, but you may change your preferences at our Cookie Centre. Please read our Privacy Policy. Both are expected to radically transform the way businesses and organizations are run in the upcoming years.

Long-time developing in a separate way, at first sight one might assume that these technologies are mutually exclusive. But that idea is rapidly changing. There are growing expectations that distributed ledgers will help enterprises finally get to grips with Big Data, which thus far is struggling with a number of challenges. They are both powerful on their own, however when combined they may bring a large number of opportunities.

Some even say that blockchain and Big Data are made for one another. The data within the blockchain is predicted to be worth trillions of dollars as it continues to make its way into banking, micropayments, remittances, and other financial services.

In this blog I will look at what the interception of these two innovations may bring. Could blockchain be the solution for the existing Big Data issues and challenges?

Big Data is one of the fastest growing sectors in the world. Every business wants to get insights into usage patterns of their consumers. Massive datasets are thereby analysed using advanced statistical models and data mining. These Big Data sets will become even more prevalent over the coming years. Big data can be analysed for insights that lead to better decisions and strategic business moves. The rise of Big Data has presented a slew of issues for both big businesses and everyday consumers.

With the growth in data good analytics is becoming all the more problematic. Some major problems to data management and analytics include so-called dirty data, inaccessible data, and privacy issues.

And as Big Data increases in size and the web of connected devices explodes, it exposes more of companies data to potential security breaches.. With the advent of Big Data, data quality management is both more important and more challenging than ever. Companies that are dealing with large datasets should ensure that the data are clean, secure and not been modified and come from an authentic source.

They have to make sure that the latest version is synchronized among all of the data centres in real time. It should also be ensured that these data are accessible. For most, however, the data silos are still a major issue and a full company-wide digital transformation is still more concept that reality.

Blockchain and Big Data: two sides of the same coin. Main question is: how do both technologies relate to each other, if any? Notwithstanding blockchain has not been explored extensively in aspects of Big Data management and analytics, both technologies could and should be seen as two sides of the same coin. While blockchain is focused on recording validating data data integrity , data science analyses data for actionable insight, making predictions from large amounts of data prediction.

While blockchain is changing data management, the latter is transforming the nature of transactions. What may Blockchain bring? Securing and interpreting such large amounts of information is not an easy task. Blockchain could be seen as an ideal solution to address many of the challenges of Big Data management and analytics.

Blockchain technology has three essential properties: Decentralization, Immutability, and Integrity. Decentralized The biggest advantage of blockchain is that it is decentralized. No single person or company controls data entry or its integrity; however, the immunity of the blockchain is verified continuously by every computer on the network.

Through its decentralized system, blockchain technology ensures the security and privacy of data. Through decentralized consensus algorithm and cryptography, blockchain validates data making it almost impossible to be manipulated due to the huge amount of computing power that will be required. Distributed Blockchain is a distributed database or ledger system that records economic transactions such that they cannot be manipulated. The distributed network system also means the same transaction is shared network-wide, making it secure by design.

It cannot be forged due to the network architecture. As the blockchain is secure it can be used to prevent hacking and data leaks. The process is also much more transparent because nothing can be changed without the approval of every server in the network, everyone can see what changes are being made. This makes it much more difficult for mistakes and fraudulent transactions to occur.

Immutable Furthermore, validated data generated via blockchain technology comes structured and complete plus the fact it is immutable.

As such, once a transaction has been recorded, it can never be changed. Information remains in the same state for as long as the network exists. Immutability of data is of utmost importance to the corporations which are concerned with Big Data. If the data set that needs to be scrutinized is modified in any way, the resulting analysis is bound to be of little value. Where Blockchain can help Big Data The combination of blockchain technology and Big Data could deliver a number of interesting opportunities.

There are several ways blockchain may be of help for Big Data management esp. This technology has the most potential in the quality of the data. What this means is the data being captured and validated by big businesses on the blockchain will become far more valuable for companies. Blockchains will give you greater confidence in the integrity of the data you see. Immutable entries, consensus-driven timestamping, audit trails, and certainty about the origin of data e.

Blockchain provides a seamless way to conduct data integrity and audit trails, since it ascertains the origin of data through its linked chains.

Blockchain ensures trust of data by maintaining a decentralized ledger. Data recorded on the blockchain are trustworthy because they must have gone through a verification process which ensures its quality. Data integrity is ensured when details of the origin and interactions concerning a data block are stored on the blockchain and automatically verified or validated before it can be acted upon.

It also provides for transparency, since activities and transactions that take place on the blockchain network can be traced. Manage Data Sharing A blockchain-based Big Data system would allow providers to share records with any other sector with an interest without the exponential increase in risk factors that comes a network of different data silos.

In this regard, data gotten from data studies can be stored in a blockchain network. This way, project teams do not repeat data analysis already carried out by other teams or wrongfully reuse data that is already been used. Also, a blockchain platform can help data scientists monetize their work, probably by trading analysis outcomes stored on the platform. Preventing Malicious Activities Because blockchain uses consensus algorithms to verify transactions, it is impossible for a single unit to pose a threat to the data network.

Because the network is so distributed, it makes it almost impossible for a single party to generate enough computational power to alter the validation criteria and allow unwanted data in the system. To alter the blockchain rules, a majority of nodes must be pooled together to create a consensus. So, it is making an almost impossible task for cybercriminals to access and manipulate data on a large scale.

Predictive Analysis Blockchain data just like other types of data can be analysed to reveal valuable insights into the behaviours, trends etc. As such they can be used to predict with good accuracy future outcomes of events like customer preferences, customer lifetime value, dynamic prices, and churn rates as it relates to businesses. With blockchain, banks and other organizations that require real-time analysis of data in large scale can observe changes in data in real time making it possible to make quick decisions.

What is more, blockchain provides structured data gathered from individuals or individual devices. And due to the distributed nature of blockchain and the huge computational power available through it, data scientists even in smaller organizations can undertake extensive predictive analysis tasks.

This is, however, not limited to business insights as almost any event can be predicted with the right data analysis whether it is social sentiments or investment markers. The advantages of integrating blockchain with Big Data are many. There is a wide range of benefits that blockchain technology is capable of serving the data analytics systems. Blockchain will make Big Data more valuable because it ensures data quality, accessibility and security. More quality data with more insights means more value.

This enables better management of huge volumes and variety of information that keeps flowing in for businesses. Enhanced data quality The technology brings innovations to data storage. By substituting the traditional storage methods with blockchain, businesses can enhance data quality as it is complete and structured.

Moreover, the integration of blockchain into a Big Data analytics solution strengthens its core by eliminating its weak points. This increases accuracy and facilitates comprehensive analysis to deliver rich and reliable insights for the business. When the data captured by big business is more secure, more trusted, and more accessible, it will become easier for companies to make decisions based on their insights. Strengthen data security Perhaps the biggest benefit that this technology serves to Big Data analytics relates to the security of the information that resides within the blockchain.

The system is decentralized, which means that there is no single person who holds control and it cannot be altered without the approval of everyone involved. This renders transparency into the entire system as well as alleviates the risk of fraudulent activities.

Fraud prevention In the financial services industry, Big Data has not yet solved the difficulties of detecting fraud and assessing risk. This is primarily because existing detection and assessment methods depend on historical data. The blockchain technology allows the financial institutions check every transaction real-time. Thus said, instead of analysing the records of the fraud that already happened, the banks are able to identify risky or fraudulent transactions on the fly and prevent the fraud entirely.

If financial institutions can harness blockchain as a means of conducting transactions, they will finally be able to evaluate risk and identify suspicious patterns in real time. This will help to protect banks and their customers from fraud. Streamlining of Big Data By storing data on a decentralised ledger Big Data companies could process all data much quicker and more efficient, compared to centralised solutions. It will also speed up the transaction process making it almost instantaneous and reduce the cost of money transfers by eliminating the barriers of security and risk checks involved.

Facilitate data access Another way in which blockchain can power up Big Data and analytics is by streamlining the access to data. Users across various departments within the organizations can be made a part of the blockchain, where they can reach the data required for the analysis process.

Blockchain-based access control management for Decentralized Online Social Networks

Clearlake Capital Group has completed its previously announced acquisition of Quest Software , a global cybersecurity, data intelligence, and IT operations management software provider, from Francisco Partners. Terms of the transaction were not disclosed. It comes with extended support. This is good for organisations that require multi-departmental analytics environments, perform machine learning or AI in the database, or have complex requirements for data integration or virtualization. Keepit, a cloud backup and recovery supplier with an independent vendor-neutral and blockchain-based cloud dedicated to SaaS data protection, announced its software now includes support for Microsoft Azure Active Directory AD.

Search Form

Welcome to Finextra. We use cookies to help us to deliver our services. We'll assume you're ok with this, but you may change your preferences at our Cookie Centre. Please read our Privacy Policy. Both are expected to radically transform the way businesses and organizations are run in the upcoming years. Long-time developing in a separate way, at first sight one might assume that these technologies are mutually exclusive. But that idea is rapidly changing. There are growing expectations that distributed ledgers will help enterprises finally get to grips with Big Data, which thus far is struggling with a number of challenges.

A Blockchain-based Access Control for Big Data

Loom token migration. This book an invaluable collection of primary sources in translation, aimed at students and academics alike. Simplify and accelerate your migration and modernization with guidance, tools, and resources. Every NFT is unique, that's what non-fungible means!

Blockchain-Based Privacy Protection Scheme for IoT-Assisted Educational Big Data Management

The protocol also tweeted early Thursday that "all funds have been restored and Wormhole is back up," following a Solana-side mint function exploit. This week's incident is the fourth largest crypto theft of all time and the second largest decentralized finance cyberattack on record, according to blockchain security firm Elliptic. Earlier, the platform indicated it had issued a fix for a detected flaw and was working to "get the network back up as soon as possible. Wormhole , at the time of publication, indicated that its team had addressed its Ethereum losses and gotten the portal back online. It stated earlier: "All funds are safe. A spokesperson for the protocol did not immediately respond to Information Security Media Group's request for additional details about the incident.

Blockchain-Based Access Control and Data Sharing Mechanism in Cloud Decentralized Storage System

Cyber-Physical-Social System CPSS big data is specified as the global historical data which is usually stored in cloud, the local real-time data which is usually stored in the fog-edge server FeS of the mobile terminal devices or sensors, and the social data which is usually stored in the social data server SdS , moreover adopts a centralized access control mechanism to offer users' access strategy which can easily cause CPSS big data to be tampered with and to be leaked. In BacCPSS, account address of the node in blockchain is used as the identity to access CPSS big data, the access control permission for CPSS big data is redefined and stored in blockchain, and processes of authorization, authorization revocation, access control and audit in BacCPSS are designed, and then a lightweight symmetric encryption algorithm is used to achieve privacy-preserving. Finally, a credible experimental model on EOS and Aliyun cloud is built. N2 - Cyber-Physical-Social System CPSS big data is specified as the global historical data which is usually stored in cloud, the local real-time data which is usually stored in the fog-edge server FeS of the mobile terminal devices or sensors, and the social data which is usually stored in the social data server SdS , moreover adopts a centralized access control mechanism to offer users' access strategy which can easily cause CPSS big data to be tampered with and to be leaked. AB - Cyber-Physical-Social System CPSS big data is specified as the global historical data which is usually stored in cloud, the local real-time data which is usually stored in the fog-edge server FeS of the mobile terminal devices or sensors, and the social data which is usually stored in the social data server SdS , moreover adopts a centralized access control mechanism to offer users' access strategy which can easily cause CPSS big data to be tampered with and to be leaked. Global Information and Telecommunication Institute. Overview Fingerprint. Abstract Cyber-Physical-Social System CPSS big data is specified as the global historical data which is usually stored in cloud, the local real-time data which is usually stored in the fog-edge server FeS of the mobile terminal devices or sensors, and the social data which is usually stored in the social data server SdS , moreover adopts a centralized access control mechanism to offer users' access strategy which can easily cause CPSS big data to be tampered with and to be leaked.

Blockchain Explained

Press releases. Fujitsu today announced the development of software to create secure data exchange networks. With a proprietary data access control technology it has developed, Fujitsu aims to promote interchanges of data accumulated by various organizations and companies.

Journal of Cloud Computing volume 10 , Article number: 35 Cite this article. Metrics details. Through virtualization and resource integration, cloud computing has expanded its service area and offers a better user experience than the traditional platforms, along with its business operation model bringing huge economic and social benefits. However, a large amount of evidence shows that cloud computing is facing with serious security and trust crisis, and building a trust-enabled transaction environment has become its key factor. The traditional cloud trust model usually adopts a centralized architecture, which causes large management overhead, network congestion and even single point of failure.

Consequently, the performance becomes a concern for blockchain-PHR integration because of the blockchain performance issues in the past. Thus, this article presents the performance analysis of the blockchain-based PHR system to ensure the usability in practice. The proposed blockchain-based PHR system prototype is implemented and the architectural model for the blockchain-based PHR system is also constructed. The key parameters for the architectural model are extracted from the prototype. Experiments are conducted with various data sizes including , KB, 2, 8 and 32 MB. The result of simulating the architectural model shows that the proposed blockchain-based PHR system can response within 4 min for 60, accesses each day. The performance results indicated that the proposed blockchain-based PHR system can work within the emergency response time of 8 min and it is usable with an efficient computational cost.

A peer-reviewed article of this Preprint also exists. Kebande, V. Sensors , 21 ,