Название: Building Secure Business Models Through Blockchain Technology: Tactics, Methods, Limitations, and PerformanceАвтор: Shweta Dewangan, Sapna Singh Kshatri
Издательство: IGI Global
Год: 2023
Страниц: 360
Язык: английский
Формат: epub (true)
Размер: 26.9 MB
Blockchain technology provided a buzz-seeking opportunity for all industries to implement improved corporate procedures and trust-building. Still, some industries, such as the banking sector, may view it as a disruptive technology that must be adopted. A transaction ledger's contents can be verified, maintained, and synchronized by community members using blockchain technology. A transaction can never be changed or removed from the blockchain; updates may only be made by participants in the system. Its distributed database cannot be manipulated, disrupted, or hacked in the same manner as conventional, user-controlled access systems and centralized databases. Building Secure Business Models Through Blockchain Technology: Tactics, Methods, Limitations, and Performance studies and explores the status of blockchain technology and, through the latest technology, builds business models to secure the future direction in the field of business. This book discusses the tactics and methods, as well as their limitations and performance. Covering topics such as AI-based efficient models, digital technology and services, and financial trading, this premier reference source is a valuable resource for business leaders and managers, IT managers, students and educators of higher education, entrepreneurs, government officials, librarians, researchers, and academicians.
Blockchain is a decentralized ledger with permanently recorded transactions maintained by a computer system that is not controlled by a single entity. Using a cryptographic chain allows for the privacy of each piece of data to be protected. The term “blockchain” is derived from this. As a result, the blockchain can be trusted to provide a safe and automated way of data transfer. A transaction's initial portion generates a block. Thousands of thousands, if not millions, of machines throughout the network, verify this block. The system-wide persistent chain is then expanded to include the validated block. The result is a fresh document with a distinctive background. To make a single bogus record, one would need to spoof the entire chain millions of times. This is so unlikely that it defies logic that it could happen. Furthermore, none of these has any accompanying costs. This innovation can replace all current business methods and models that rely on charging a single price for any trade between two parties since there needs to be a clear leader on the street.
Chapter 1 introduces blockchain technology use in different sectors. Blockchain was developed to support Bitcoin, a cryptocurrency that lacks confidence. However, many companies and stakeholders view technology as a promising means of resolving current business issues and upending established industries. The distributed ledger, known as the blockchain, has much potential for the financial services sector. Most blockchain use cases have been found in the financial industry. When creating new insurance products, insurers can benefit from blockchain technology—expansion of goods and services, fraud detection, price rises, and cost-cutting. With blockchain technology, businesses can readily verify facts, access vast talent pools, and reduce their dependency on outside sources of labor. Banks, governments, and companies want in on the venture capital action that blockchain has opened up. This article presents a novel approach or methodology for utilizing blockchain technology to manage businesses or other industries.
Chapter 2 involves a Convolutional Neural Network; this study aims to create a model for putting traffic signs in an image into many different groups using a (CNN) and the Keras library to find the signs. Traffic Sign Recognition aims to create a Deep Neural Network (DNN) to sort traffic signs into groups. We should use the German Traffic Sign Dataset to train the model to determine what traffic signs mean from natural images. This data should be pre-processed first to get the most out of the model. After choosing the model architecture, fine-tuning, and training, the model will be tested on new images of traffic signs found on the web. Since we need to classify images, we use a Convolutional Neural Network, which is a common choice for this problem. Tensor Flow library is used to write the code in Python. With 95% accuracy, our CNN model could recognize traffic signs and put them in the correct category. This model's graphical user interface (GUI) makes it easy to understand how signs are put into different classes.
Chapter 3 discussed the future estimation of business through blockchain technology. This article looks at blockchain technology's potential, current state, and how some of its parts could change how “business as usual” is done in different fields. This study combines the theoretical background of many research articles published in respected scientific journals over the past ten years and some of the findings to make our review easier and cover the rapidly growing blockchain domain. Based on a structured, systematic review and thematic content analysis of the current literature, the researcher suggests a thorough classification of blockchain-enabled applications in a wide range of industries, such as supply chain, business, health, IoT, privacy, data management, and others.
Chapter 5 provides how telecom sectors can grow through blockchain. As TRAI had asked, the study looked at how blockchain technology could change the telecom industry. This made the telecom industry adopt blockchain technology to fix some problems. Blockchain provides security, transparency, immutability, and control from the point of transaction. It also has immediate and tangible benefits for roaming and settlements, identity management, mobile number portability, SLA monitoring, preventing phone theft, and creating a single source of truth of networks. As 5G participants use blockchain, other use cases will arise, such as a marketplace for telecom infrastructure, payments through mobile wallets, and device identity and security management.
Chapter 7 presents the financial institution which using blockchain technology for many years. The combination of Artificial Intelligence and Blockchain Technology will be more potent in the following decades. Blockchain Technology is stable and secure. Thus, countries are adopting it in financial trading.
Chapter 9 discussed decentralized financial applications (DeFi) use intelligent contracts and permissionless blockchain technologies.
Chapter 11 manages blockchain stores of every network-generated transaction. Blockchains are encrypted copies of every register. Decentralized data is blockchain technology's main feature—a decades-long blockchain-based secure database platform.
Chapter 13 discussed blockchain's high security ensures data integrity. Cryptography encryption in the blockchain system protects data against attackers, fraud, manipulation, and theft, providing data integrity, confidentiality, availability, security, efficiency, and user privacy. Blockchain communications provide bilinear data integrity. Client, KGC, cloud storage server and blockchain make up the blockchain-based data integrity verification framework. Data integrity verification involves setup, processing, and verification. Simulations reveal that the blockchain approach for IoT data integrity outperforms the high-efficiency blockchain-based cloud data integrity verification scheme.
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