scholarly journals Study on Internet Finance Credit Information Sharing Based on Block Chain Technology

2018 ◽  
Vol 14 (2) ◽  
pp. 81 ◽  
Author(s):  
Maoran Zhu ◽  
Xin Liu
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Privacy ◽  
Distributed Database ◽  
Financial Credit ◽  
User Data ◽  
Block Chain ◽  
Distributed Database System ◽  
Credit Data ◽  
Big Data Technology

With development of Big Data technology these years, Internet financial companies in China started trying using big data technology to do credit investigation instead of traditional methods. But there is some limitation and problem in terms of data acquisition channel, information asymmetry and data privacy protection, etc. Block chain, characterized in unalterability and decentralization comes into people's sight. This paper will introduce block chain technology, explore the use of block chain technology in Internet financial credit investigation, and put forward an internet financial credit data sharing model based on block chain, which mainly composed by the Fin-tech Federate Servers group (FFS), the user data storage structure and a distributed database system (DDBS). By combining DPoS and re-encryption technology, the model has the characteristics of non-tampering, authorized access and convenient accountability. Through this model, the user data is recorded by the trusted agent, encrypted by asymmetric encryption technology, and anchored to the chain of the block periodically.

scholarly journals Challenges of Credit Reference Based on Big Data Technology in China

2021 ◽  
Author(s):  
Cheng-yong Liu ◽  
Chih-Chun Hou
Keyword(s):  
Big Data ◽  
Information Security ◽  
Secure Communication ◽  
Distributed Storage ◽  
Blockchain Technology ◽  
Financial Credit ◽  
Credit Data ◽  
Point To Point ◽  
The Individual ◽  
Big Data Technology

AbstractBig data-based credit reference system gradually attracts wide attention due to its ad-vantages in remedying the shortages of traditional credit reference and dealing with new challenges arising from financial credit management. Nevertheless, this new method is also adapted through different studies and experiments to be problematic with island of credit information and information security. Some researchers begin exploring the possibility of applying blockchain technology to the individual credit reference field. The business links in the individual credit reference can be innovated through the blockchain mechanism so that credit data from different industries get collected through peering points, secure communication and anonymous protection on the basis of such techniques as distributed storage, point-to-point transmission, consensus mechanism and encryption algorithm. In this way, it is feasible to solve island of information and enhance the protection of user information security. A promising future can be expected about the big data-based credit reference, but there are also many problems with blockchain-based credit reference in China.

scholarly journals A review: evolution of big data in developing country

2019 ◽  
Vol 3 (1) ◽  
pp. 30-37
Author(s):  
Bayu Prasetyo ◽  
Faiz Syaikhoni Aziz ◽  
Kamil Faqih ◽  
Wahyu Primadi ◽  
Roni Herdianto ◽  
...  
Keyword(s):  
Developing Countries ◽  
Big Data ◽  
Developing Country ◽  
Data Storage ◽  
Human Life ◽  
Large Data ◽  
Big Data Technology

The development of technology from year to year is increasingly rapid and diverse. All systems that exist in human life began to be designed with technology that requires large data storage. Big Data technology began to be developed to accommodate very large data volumes, rapid data changes, and very varied. Developing countries are starting to use Big Data a lot in developing their systems, such as healthcare, agriculture, building, transportation, and various other fields. In this paper, it explains the development of Big Data applied to the sectors previously mentioned in developing countries and also the challenges faced by developing countries in the process of developing their systems.

scholarly journals The Construction and Thinking of Cloud Computing and Big Data Technology in Smart Campus

2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Information Technologies ◽  
Rapid Development ◽  
Smart Campus ◽  
Huge Data ◽  
New Information ◽  
Big Data Technology

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>

An Intelligent Approval System for City Construction based on Cloud Computing and Big Data

2020 ◽  
pp. 248-263
Author(s):  
Guanlin Chen ◽  
Erpeng Wang ◽  
Xinxin Sun ◽  
Yizhe Lu
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Response Speed ◽  
Distributed Database ◽  
Cloud Services ◽  
Distributed Programming ◽  
Case Based Reasoning ◽  
Development Platform ◽  
Full Text Retrieval ◽  
City Construction

On the theoretical basis of cloud services, big data technology and case-based reasoning technology (CBR), the authors propose an Intelligent Approval System for City Construction (IASCC). The paper introduces the concept of ‘case approval cloud' and puts forward the city construction approval model based on CBR, by which the storage and computation of the urban construction approval data are concentrated in the cloud. In this system, the authors use the distributed database of HBase, making the data storage capacity of the system with high scalability, design the intelligent approval system based on CBR using the distributed programming framework of MapReduce, making full use of the large amount of historical approval data, and use the distributed full-text retrieval system of SorCloud to retrieve the approval data with a high response speed. IASCC adopts Hadoop as the development platform, using HBase, Solr and MapReduce technology to complete the prototype development of an intelligent approval system. Finally, the authors give the implementation of the system and the performance tests of some key modules.

PcAVP - Adaptable Vertical Partitioning Algorithm Based on Privacy Constraint for Distributed Database System

2013 ◽  
Vol 303-306 ◽  
pp. 2139-2143
Author(s):  
Jie Jiang ◽  
Zhu Yan Gu ◽  
Tie Ming Chen
Keyword(s):  
Privacy Protection ◽  
Data Privacy ◽  
Distributed Database ◽  
Constraint Checking ◽  
Vertical Partitioning ◽  
Data Privacy Protection ◽  
Partitioning Algorithm ◽  
Distributed Database System ◽  
Specific Number ◽  
Best Fit

Vertical partitioning is a process of generating fragments, each of which is composed of attributes with high affinity. It is widely used in the distributed database to improve the efficiency of system by reducing the connection between the table access operations. The current research on vertical partitioning is mainly focused on how to measure the "affinity" to get the best-fit vertical partitioning and the n-way vertical partitioning which support generating the specific number of fragments required by the user. In this paper, we propose a vertical partitioning algorithm based on privacy constraint. It supports both the best-fit vertical partitioning and the n-way vertical partitioning. It also provides the data privacy protection by privacy constraint checking. We conduct several experimental results to show that our algorithm not only keeps higher efficiency, but also provides data privacy protection.

scholarly journals Implementasi Sistem Interkoneksi Basis Data Terdistribusi Menggunakan Socket API

2017 ◽  
Vol 1 (1) ◽  
pp. 1-4
Author(s):  
Ary Yulianto
Keyword(s):  
Information System ◽  
Big Data ◽  
Human Resources ◽  
Distributed Databases ◽  
Distributed Database ◽  
Database System ◽  
Master Data ◽  
Distributed Database System ◽  
The Moment ◽  
Asset Data

  Majelis Pendidikan Dasar dan Menengah Pimpinan Daerah Kabupaten Magelang needs information about the development of the school. The necessary data include data on human resources, asset data and data of their students. At the moment the data is obtained manually by looking to the schools. With the development of information technology is now expected to have a school information system that can provide information quickly and accurately. Data on each school if put into one large server or big data can be used to analyze the data. The purpose of this research is to implement the interconnection of distributed database system using the socket API. It is used to provide master data of all schools under Persyarikatan Muhammadiyah. To support the analysis of the data interconnection of distributed databases, socket API technology is used. With a system like this then the communications database can be connected so that the school's data will be sent directly through the socket API and the data will automatically be processed by the webservice in the server middleware and will be utilized in the next process.

scholarly journals Research on Sharing Economic Development of “Big Data + Block Chain”——Based on Industry Convergence Theory

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Haiying Liu
Keyword(s):  
Economic Development ◽  
Big Data ◽  
Sharing Economy ◽  
Internet Technology ◽  
Convergence Theory ◽  
Industry Convergence ◽  
Block Chain ◽  
Technology And Communication ◽  
Further Development ◽  
Big Data Technology

Sharing economy as an important product of the Internet Era, its essence is to rely on Internet technology, especially big data technology to reuse the idle resources of society and creating new market value. However, with the increasing scope of the sharing economy, the problems of data security, circulation, sharing and privacy protection are gradually emerging, and big data technology has become the biggest bottleneck for further development of shared economy. The block chain technology is composed of a variety of technology and communication protocol to form a new Internet architecture, it through cryptographic sharing, distributed books and other feathers to provide new methods and ideas for data distribution and sharing and complementary with big data technology. Therefore, through the combination of block chain technology and big data technology, they can subvert the traditional shared economic business model and provide a new opportunity for sharing economic development.

scholarly journals Big Data on Machine Learning – A Review

2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Balasree K ◽  
Dharmarajan K
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Data Storage ◽  
Data Analytics ◽  
Rapid Development ◽  
Learning Algorithms ◽  
Big Data Analytics ◽  
Machine Learning Algorithms ◽  
Data Sets ◽  
Big Data Technology

In rapid development of Big Data technology over the recent years, this paper discussing about the Machine Learning (ML) playing role that is based on methods and algorithms to Big Data Processing and Big Data Analytics. In evolutionary fields and computing fields of developments that both are complementing each other. Big Data: The rapid growth of such data solutions needed to be studied and provided to handle then to gain the knowledge from datasets and extracting values due to the data sets are very high in velocity and variety. The Big data analytics are involving and indicating the appropriate data storage and computational outline that enhanced by using Scalable Machine Learning Algorithms and Big Data Analytics then the analytics to reveal the massive amounts of hidden data’s and secret correlations. This type of Analytic information useful for organizations and companies to gain deeper knowledge, development and getting advantages over the competition. When using this Analytics we can predict the accurate implementation over the data. This paper presented about the detailed review of state-of-the-art developments and overview of advantages and challenges in Machine Learning Algorithms over big data analytics.

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