Self-service Business Intelligence Tools For Analyzing Cryptocurrency Trends

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Self-service Business Intelligence Tools For Analyzing Cryptocurrency Trends

Self-service Business Intelligence Tools For Analyzing Cryptocurrency Trends

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By Zeinab Shahbazi Zeinab Shahbazi Scilit Google Scholar View Publications 1 and Yung-Cheol Byun Yung-Cheol Byun Scilit Google Scholar View Publications 2, *

Department of Computer Engineering, Master of Electronics Engineering, Institute of Information Science and Technology, Jeju National University, Jeju 63243, Republic of Korea

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Submission received: 3/10/2022 / Revised: 10/11/2022 / Approved: 20/11/2022 / Published: 23/11/2022

Cryptocurrency, often known as virtual or digital currency, is a secure platform and a central part of the blockchain that has attracted a lot of interest recently. Using blockchain technology, Bitcoin transactions are recorded in blocks that provide detailed information about all financial transactions. Artificial intelligence (AI) has significant applicability in many fields due to the abundance and processing power of big data. One of the biggest problems is the lack of explanations of AI algorithms in current decision-making standards. For example, there is no deep learning-based reasoning or control for the system’s input or output processes. More precisely, the bias of adversary attacks on process interface and learning characterizes existing AI systems. This research proposes an AI-based trust architecture that utilizes decentralized blockchain features such as smart contracts and trust oracles. This system also determines the decentralized consensus of AI predictors using artificial intelligence, enabling secure cryptocurrency transactions and using blockchain technology and transactional network analysis. Using artificial intelligence for in-depth network research, the primary goal of this system is to improve the performance of the Bitcoin network in terms of transactions and security. Compared with other state-of-the-art systems, the results show that the proposed system can achieve a highly accurate result.

The combination of blockchain and artificial intelligence has emerged as one of the disruptive technologies that directly affects people’s lives. These technologies are one of the most important forces of global innovation. In recent years, the world has had to deal with a brand new trading system called cryptocurrency. To carry out transactions through this network, this system is built on a distributed, decentralized blockchain network. With the rapid development of blockchain technology, cryptocurrencies have also gained popularity and interest. In the second quarter of 2020, nearly 7,000 different types of cryptocurrencies were traded frequently, with a market capitalization of more than $300 billion. Artificial intelligence technology has a versatile impact on different industries and sectors. The complex design of AI reflects the results of more than 70 years of research and studies in a field with many ethical and security concerns [1, 2, 3, 4]. According to [5, 6, 7, 8], adversary attacks and bias are two basic disadvantages of artificial intelligence systems. Bias sensitivity increases in some data to allow AI systems to make accurate decisions, but it doesn’t work well for the entire population. In addition, one of the biggest problems in recent years, especially in critical areas, has been the lack of data interpretation in artificial intelligence systems. For example, in terms of chatbots and object recognition, the proposals of deep learning systems are accepted without any assumptions. Games with the possibility of a wrong guess are not particularly strict. The situation is urgent, directly affects significant assets or lives, and remains a concern when it comes to incorrect predictions and decision-making in healthcare systems, security or finance.

Self-service Business Intelligence Tools For Analyzing Cryptocurrency Trends

Proof of Work (PoW). PoW is one blockchain consensus method for adding new transactions to the ledger. Checking events and adding new blocks to the chain are the first goals. PoW initiates a process where participants transact online and receive rewards. Individuals are identified as miners and mining as an activity. Digital tokens are sent over the network between miners, and in a decentralized network, all transactions are compiled into a block. The purpose of this whole procedure is to sort blocks, verify transactions and reach a small consensus.

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Proof of Presentation (PoS): A consensus protocol to solve the energy usage problem is called PoS. Stakeholders in the blockchain network can create new blocks thanks to this protocol. The protocol selects validators based on several criteria, such as delegated validators and high-frequency event validators. In addition to being more energy efficient than PoW, PoS also solves some security issues by avoiding the distribution of validators who own the original money on the blockchain. The creation of new blocks is delayed if validation fails. When it comes to change detection and data streaming, PoS provides latency tolerance in AI applications.

The digital currency revolution is mentioned [9, 10, 11]. Various variants of central bank digital currencies (CBDCs) have been considered to reflect the decision-making, risks and benefits of this system. An overview of bank-backed digital money is given in [12]. This report analyzes the current CBDC controversies, focusing on states opposed to CBDC implementation. The authors of the book [13] evaluate the new situation related to the mining power of Bitcoin and Ethereum. A total of six scenarios are proposed for the network data parameters collected about the performance of the mining equipment. The results show that the total demand capacity of the blockchain is limited by the efficiency of the mining rigs. The energy efficiency of cryptocurrency mining has been mentioned in publications [14, 15]. This method for Bitcoin, Ethereum, Litecoin and Monero has estimated the minimum energy needed to create the value element of the digital asset in terms of energy consumption. In [16], the authors mainly focused on Bitcoin mining and environment in stable countries. At the beginning of the process, environmental efficiency index (EPI), energy price, temperature, human capital and legal constraints are taken into account. The latest research on cryptocurrencies and blockchain is in [17, 18]. The history, definition and factors affecting value, legal status and other aspects of cryptocurrencies were discussed.

The rest of this article is organized as follows. Part 2 provides a comprehensive literature review of the AI ​​and cryptocurrency framework. In this framework, the information retrieval mechanism based on system events is presented in Section 3. The results and environmental data of the proposed approach are presented in Section 4, and we conclude this paper in Section 5.

This section briefly describes the technology of information discovery and artificial intelligence using blockchain architecture. There are two separate sections for Blockchain AI and Cryptocurrency-Based Exchange Security.

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According to [19, 20], the blockchain framework is a very popular secure framework for transactions between users and many different companies. Blockchain technology is a decentralized network that powers markets with multiple artificial intelligence components, including data, processing power, and algorithms. Decentralized artificial intelligence is a new idea to combine blockchain and artificial intelligence, as mentioned in [19, 21, 22, 23]. This method raises the bar for artificial intelligence innovation and adaptability. In addition, blockchain contributes to the transparency, trustworthiness, and discretion of AI due to its publicly available database, which increases the trust and privacy of the framework [ 24 , 25 , 26 , 27 , 28 ]. Secure data sharing, an artificial intelligence revolution in terms of big data and the gold standard of the data-based services economy, is another benefit of blockchain. In terms of decision-making, smart contract-based systems produce an accurate and reliable system that validates and validates blockchain nodes. Participants in the organization cannot opt ​​out of this type of choice or track and follow. Well-known distributed storage technologies include Filecoin [29], Storj [30], Interplanetary File System [31] and BigChainDB [32]. Blockchain for AI problems is reviewed in [33, 34]. Platform and AI-oriented blockchain application development was the main focus. Blockchain challenges and implications for artificial intelligence

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