A Deep Learning Application System Based on Blockchain Technology for Clicks-And-Mortar Businesses

2019 ◽  
Author(s):  
Hsin-Te Wu ◽  
Chun-Yi Lu
Keyword(s):  
Deep Learning ◽  
Application System ◽  
Blockchain Technology

Deep learning based Blockchain solution for preserving privacy in future vehicles

2020 ◽  
pp. 1-14
Author(s):  
Varsha R ◽  
Meghna Manoj Nair ◽  
Siddharth M. Nair ◽  
Amit Kumar Tyagi
Keyword(s):  
Deep Learning ◽  
Autonomous Vehicles ◽  
Recommendation System ◽  
Privacy Preserving ◽  
Smart Devices ◽  
The Road ◽  
Blockchain Technology ◽  
Technological Advances ◽  
Previous Decade ◽  
Smart Things

The Internet of Things (smart things) is used in many sectors and applications due to recent technological advances. One of such application is in the transportation system, which is of primary use for the users to move from one place to another place. The smart devices which were embedded in vehicles are useful for the passengers to solve his/her query, wherein future vehicles will be fully automated to the advanced stage, i.e. future cars with driverless feature. These autonomous cars will help people a lot to reduce their time and increases their productivity in their respective (associated) business. In today’s generation and in the near future, privacy preserving and trust will be a major concern among users and autonomous vehicles and hence, this paper will be able to provide clarity for the same. Many attempts in previous decade have provided many efficient mechanisms, but they all work only with vehicles along with a driver. However, these mechanisms are not valid and useful for future vehicles. In this paper, we will use deep learning techniques for building trust using recommender systems and Blockchain technology for privacy preserving. We also maintain a certain level of trust via maintaining the highest level of privacy among users living in a particular environment. In this research, we developed a framework that could offer maximum trust or reliable communication to users over the road network. With this, we also preserve privacy of users during traveling, i.e., without revealing identity of respective users from Trusted Third Parties or even Location Based Service in reaching a destination. Thus, Deep Learning based Blockchain Solution (DLBS) is illustrated for providing an efficient recommendation system.

scholarly journals Perspective Cryptocurrency Projects Supported by China

2019 ◽  
Vol 7 (2) ◽  
pp. 37-44
Author(s):  
N. Asadova
Keyword(s):  
Deep Learning ◽  
Research And Development ◽  
Positive Attitude ◽  
Chinese Government ◽  
Bank Of China ◽  
Digital Currency ◽  
Blockchain Technology ◽  
International Consulting ◽  
Strict Regulation ◽  
Research Institute

In this article are discussed the most perspective cryptocurrency and blockchain projects that China is investing in. After the regulations regarding cryptocurrencies that is put forth by China, the Chinese government decided to create several financial bodies to regulate and develop the cryptocurrency. Despite the strict regulation of cryptocurrencies, China has been significantly investing in blockchain projects. China has developed the Digital Currency Research Institute (DCRI) of the People’s Bank of China — a research body under the aegis of PBOC that focuses on the research and development of digital currencies and blockchain-related technologies. China actively supports more than 40 platforms, mostly in such fields as AI, Deep Learning and Software. The Chinese government has shown a positive attitude towards blockchain technology. Blockchain and cryptocurrency come hand-in-hand (except a private chain where a token is unnecessary). In the nearest future, China plans to introduce a blockchain to the most different spheres. For this purpose, there will even double the volume of investment to 3 billion dollars, since the second quarter of 2018. “This technology can transform many spheres of our life. As soon as in the country pursue powerful technological policy, it is sure that even more companies will begin to work in the field of the blockchain” —the partner of the international consulting company PwC in Shanghai Chongg Chong Yin commented to journalists.

scholarly journals Blockchain Scalability Enhancement using Parallel Miners Selection

2019 ◽  
Vol 8 (12) ◽  
pp. 4356-4360
Keyword(s):  
Credit Card ◽  
Large Scale ◽  
Application System ◽  
Good Utilization ◽  
Blockchain Technology ◽  
Card System ◽  
The Difference ◽  
Financial Transactions

Apart from the good utilization of the blockchain, there are different challenges that are there at the blockchain system. The problem is that despite several advantages of a blockchain, the current blockchain networks cannot support at large scale application system. Some of the major problems that blockchain technology suffering from are scalability, privacy, and interoperability. The major issue of blockchain technology is scalability. The problem of scalability means that the capacity to process a transaction on a blockchain is very limited and slow. If we think about financial transactions and we compare the ethereum blockchain or the Bitcoin blockchain to the financial transactions provided by Visa MasterCard or any other centralized company, then we would see a difference between them. The difference is that ten to fifteen transactions per second are performed by blockchain-based decentralized cryptocurrency systems in comparison to several thousand transactions per second by a centralized credit-card system.

scholarly journals Blockchain for Deep Learning: Review and Open Challenges

2021 ◽  
Author(s):  
Muhammad Shafay ◽  
Raja Wasim Ahmad ◽  
Khaled Salah ◽  
Ibrar Yaqoob ◽  
Raja Jayaraman ◽  
...  
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Single Point ◽  
Data Provenance ◽  
Learning Models ◽  
Data Types ◽  
Consensus Protocol ◽  
Blockchain Technology ◽  
Trusted Data ◽  
Learning Frameworks

Deep learning has gained huge traction in recent years because of its potential to make informed decisions. A large portion of today's deep learning systems are based on centralized servers and fall short in providing operational transparency, traceability, reliability, security, and trusted data provenance features. Also, training deep learning models by utilizing centralized data is vulnerable to the single point of failure problem. In this paper, we explore the importance of integrating blockchain technology with deep learning. We review the existing literature focused on the integration of blockchain with deep learning. We classify and categorize the literature by devising a thematic taxonomy based on seven parameters; namely, blockchain type, deep learning models, deep learning specific consensus protocols, application area, services, data types, and deployment goals. We provide insightful discussions on the state-of-the-art blockchain-based deep learning frameworks by highlighting their strengths and weaknesses. Furthermore, we compare the existing blockchain-based deep learning frameworks based on four parameters such as blockchain type, consensus protocol, deep learning method, and dataset. Finally, we present important research challenges which need to be addressed to develop highly efficient, robust, and secure deep learning frameworks.

scholarly journals Blockchain for Deep Learning: Review and Open Challenges

2021 ◽  
Author(s):  
Muhammad Shafay ◽  
Raja Wasim Ahmad ◽  
Khaled Salah ◽  
Ibrar Yaqoob ◽  
Raja Jayaraman ◽  
...  
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Single Point ◽  
Data Provenance ◽  
Learning Models ◽  
Data Types ◽  
Consensus Protocol ◽  
Blockchain Technology ◽  
Trusted Data ◽  
Learning Frameworks

Deep learning has gained huge traction in recent years because of its potential to make informed decisions. A large portion of today's deep learning systems are based on centralized servers and fall short in providing operational transparency, traceability, reliability, security, and trusted data provenance features. Also, training deep learning models by utilizing centralized data is vulnerable to the single point of failure problem. In this paper, we explore the importance of integrating blockchain technology with deep learning. We review the existing literature focused on the integration of blockchain with deep learning. We classify and categorize the literature by devising a thematic taxonomy based on seven parameters; namely, blockchain type, deep learning models, deep learning specific consensus protocols, application area, services, data types, and deployment goals. We provide insightful discussions on the state-of-the-art blockchain-based deep learning frameworks by highlighting their strengths and weaknesses. Furthermore, we compare the existing blockchain-based deep learning frameworks based on four parameters such as blockchain type, consensus protocol, deep learning method, and dataset. Finally, we present important research challenges which need to be addressed to develop highly efficient, robust, and secure deep learning frameworks.

scholarly journals Blockchain-Based Intelligent Transportation: A Sustainable GCU Application System

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xiaomin Du ◽  
Yang Gao ◽  
Chia-Huei Wu ◽  
Rong Wang ◽  
Datian Bi
Keyword(s):  
Social Problems ◽  
Environmental Issues ◽  
Intelligent Transportation ◽  
Theoretical Framework ◽  
Multiple Stakeholders ◽  
Interpretive Structural Modeling ◽  
Application System ◽  
Blockchain Technology ◽  
The Social ◽  
The Government

The purpose of this study is to explore how to apply blockchain technology to intelligent transportation, create a hierarchical theoretical framework of intelligent transportation, and explore a sustainable application system of intelligent transportation under the blockchain. However, not only this hierarchical theoretical framework must consider unnecessary attributes and the interrelationships between the aspects and the criteria, but also the sustainable application system must be in consideration in multiple stakeholders. Hence, fuzzy set theory is used for screening out the unnecessary attributes, a decision-making trial and evaluation laboratory (DEMATEL) is proposed to manage the complex interrelationships among the aspects and attributes, and interpretive structural modeling (ISM) is used to divide the hierarchy and construct a hierarchical theoretical framework. Finally, the research develops a sustainable GCU application system for intelligent transportation under the blockchain. The results show that (1) solving social problems is the primary link, (2) economic tasks are mainly focused on smart contracts and affected by the social problems, (3) the continuous improvement of environmental issues requires a solution to social problems, and (4) the application system of blockchain in intelligent transportation needs to be built from three levels including the government layer, the company layer, and the user layer. This theoretical hierarchical framework aims to guide intelligent transportation toward the application of blockchain. This study also proposes the engagement of stakeholders for establishing a sustainable application system.

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