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Many traders believe in and use Twitter tweets to guide their daily cryptocurrency trading. In this project, we investigated the feasibility of automated sentiment analysis for cryptocurrencies. For the study, we targeted one cryptocurrency (NEO) altcoin and collected related data. The data collection and cleaning were essential components of the study. First, the last five years of daily tweets with NEO hashtags were obtained from Twitter. The collected tweets were then filtered to contain or mention only NEO. We manually tagged a subset of the tweets with positive, negative, and neutral sentiment labels. We trained and tested a Random Forest classifier on the labeled data where the test set accuracy reached 77%. In the second phase of the study, we investigated whether the daily sentiment of the tweets was correlated with the NEO price. We found positive correlations between the number of tweets and the daily prices, and between the prices of different crypto coins. We share the data publicly. Publisher's Version

Physical cash is the most liquid asset and holds high usage rates despite rapid technological advancements in the digital cash industry, especially in the context of a developing country like India. As such, Automated Teller Machines (ATMs) form an integral component of any individual's cash needs and managing the amount of cash in any given ATM is of paramount importance for any bank. ATMs are periodically filled with cash by banks, predominantly with the help of cash management agencies. Through our research we want to determine the feasibility of adding mathematical support to the current system by using Data Analysis and Machine Learning (ML). The findings of this research and modelling approaches were applied to a procured dataset which consists of data of 5 ATMs of the same bank from 2011–2017. The year, month, day, festival religion, day of the week, holiday status of yesterday, today and tomorrow were the factors that were initially analyzed and later on, average withdrawal for a given window of time in the past, the weather status and the type of holiday were the other features engineered which proved to be useful. The algorithms being tested include Lasso, Ridge, Elasticnet, Random Forest & CatBoost which is a deep learning framework. Two approaches for testing were determined, one approach was to create one model for all years in the data and another approach was to develop a model per year. In both approaches, it was found that Lasso regression outperformed all the other algorithms in contention.

In 2013, Internet money fund products led by Yu'e Bao were born. They are dependent on the Internet and attract a large number of customers with their unique marketing platform, convenient trading methods and high liquidity. At present, Alipay, NetEase, SUNING, Tencent, Baidu, JD.com and other companies have joined the ranks. Many Internet money funds are springing up in the market like bamboo shoots after a spring rain. However, against the backdrop of a marked decline in the global economy affected by the COVID-19 epidemic, the reference rate of return of various Internet money funds has plummeted, with Tianhong Yu'ebao ‘s 7-day annualized yield falling below 2% to 1.855% for the first time since its establishment. In this paper, 20 sample funds are tested by VaR model, and the corresponding evaluation is given. The analysis results show that the overall value at risk of Internet money funds is not high, so it is suitable to avoid risk, but the rate of return and VaR do not fully reflect the market law of “high risk, high return; low risk, low return”, indicating that there is still a lot of room for improvement in risk control of Internet money funds in China. The development of Internet money fund has a profound impact on the traditional fund industry and even the whole financial industry. based on this, it is particularly important to analyze the development status, operation mechanism and risk of Internet money fund. Empirical analysis through data statistical test and ARCH effect test can analyze the risk more effectively and help investors understand Internet money fund products so that they can invest better. First of all, compared with the Internet money fund, the risk of bank wealth management products is relatively higher. Second, the risk spillover of Internet money funds and bank wealth management products is asymmetric, and the risk spillover of Internet money funds to bank wealth management products is stronger. Third, Internet money funds of banking and fund departments have positive risk spillover effects on bank wealth management products, which means that Internet money funds of banking and fund departments can aggravate the risk impact on China's commercial banks.

Digital transformation forces the utilization of e-money during the economic transaction. Behind its advantages, e-money has been influenced by the inflation rate, thus accelerating the country’s money circulation. Moreover, the fragile Covid-19 economy triggers each country’s need to anticipate the circulation of e-money to deter future inflation. Therefore, this paper deployed the Backpropagation approach integrated with the Genetic Algorithm to forecast the dissemination of e-money in Indonesia by exploiting time-series Bank Indonesia (BI) data from January 2009 to December 2019. Here, 120 data with 12 variables are considered to thoroughly predict the Year 2020 circulation focusing on the previous 12 months. This study reveals that e-money circulation in Indonesia is increasing monthly in 2020. The testing result shows that the lowest mean square error (MSE) is found at 0.000035 for data training division at 90%:10%, learning rate parameter at 0.8, the combination of crossover probability and mutation at 0.4:0.6, and the total generation and population at 350 and 200, respectively. In a nutshell, Backpropagation with a Genetic Algorithm has been expected to a successful outcome for e-money circulation and provides large values compared with actual data and original BPNN.

Blockchain is a technology that has become more and more common lately. Due to the possibility to record transactions between two parties securely in the transport chain, without the intervention of a third party, it can be used successfully. The number of people who will use public transport will increase, while the number of personal vehicles will be found in traffic in smaller numbers. We can use this technology at the level of crowded localities: –to streamline transport;–to protect the environment against pollution;–and last but not least to convince the residents of the locality, but not only, to use the means of public transport. They will be stimulated with virtual coins, if they use this type of transport, made with ecological cars. First of all, the local authorities may be the ones that need to make the transport in the territory more efficient, by reducing the noxious substances, the agglomeration and the safety of the citizen. Blockchain technology will be the one to support this research.

EMV is the international protocol standard for smartcard payment and is used in over 9 billion cards worldwide. Despite the standard's advertised security, various issues have been previously uncovered, deriving from logical flaws that are hard to spot in EMV's lengthy and complex specification, running over 2,000 pages. We formalize a comprehensive symbolic model of EMV in Tamarin, a state-of-the-art protocol verifier. Our model is the first that supports a fine-grained analysis of all relevant security guarantees that EMV is intended to offer. We use our model to automatically identify flaws that lead to two critical attacks: one that defrauds the cardholder and a second that defrauds the merchant. First, criminals can use a victim's Visa contactless card to make payments for amounts that require cardholder verification, without knowledge of the card's PIN. We built a proof-of-concept Android application and successfully demonstrated this attack on real-world payment terminals. Second, criminals can trick the terminal into accepting an unauthentic offline transaction, which the issuing bank should later decline, after the criminal has walked away with the goods. This attack is possible for implementations following the standard, although we did not test it on actual terminals for ethical reasons. Finally, we propose and verify improvements to the standard that prevent these attacks, as well as any other attacks that violate the considered security properties. The proposed improvements can be easily implemented in the terminals and do not affect the cards in circulation., Comment: Accepted for IEEE S&P 2021

Today, FinTech is integrating with IoT and Artificial Intelligence to challenge banks at a very speedy pace. Fast support and better convenience are major characteristics of FinTech that makes it desirable to customers. This article covers some of the most active and prominent areas classified under the term FinTech they are: Cryptocurrency and digital cash, Smart contracts, Open banking, Blockchain technology, RegTech, InsurTech, Unbanked services, Robo-advisors, Crowd funding. This paper offers coherent research themes built on a critical assessment of the literature. This paper provides a review of the history of FinTech and the various areas under FinTech. Know-hows like Machine Learning, AI, and predictive analytics in financial services can directly affect overall business policy, revenue generation, and resource optimization.

In the evolution of the electronic money system, frequent transaction fraud has been a shadow behind the prosperity. It not only endangers the property security of users, but also hinders the development of digital finance in the world. With the development of data mining and machine learning, some mature technologies are gradually applied to the detection of transaction fraud. This paper proposes a transaction fraud detection model based on random forest. The experimental results of IEEE CIS fraud dataset show that the method of this model is better than the benchmark model, such as logistic regression, support vector machine. Finally, the accuracy of our model reached 97.4%, and the AUC ROC score was 92.7%.

Visually impaired people face extreme difficulties in recognizing paper currencies for day-to-day transactions as the texture and shape of many currencies are very similar. In this paper, an automated system for identifying the Bangladeshi banknotes using a convolutional neural network has been proposed for helping visually impaired people. A new dataset has been created consisting of more than 70,000 images of currently available Bangladeshi banknotes. The development of the system includes dataset building, creating and training the convolutional neural network model, and testing it in real-time. For verifying the efficacy of the proposed method, it has been tested in various backgrounds. The system can identify the eight banknotes used in Bangladesh with an average accuracy of 92% and exhibit the result with both textual and auditory output. Moreover, the system is invariant of the orientation and sides of notes. Visually impaired people will be able to easily use it in daily transactions.

This paper presents an overview of a first-year PhD thesis. The main idea can be expressed as a community detection issue in a real network containing data from a telecommunications operator. More precisely, mobile money transactions will be studied, with a view to detecting fraudulent ones. For this purpose, we propose to address the problem by studying different community detection approaches. Indeed, in a network, communities are constituted between users sharing common habits, therefore fraudulent transactions may appear as unusual behaviors. The originality of this work is to process real data, gathered by a telecom operator. Complex network organization is expected, making this thesis quite promising.

Transactions (TX) sent and executed by a public Blockchain (BC) need to pay a TX fee. The fee is relative to the resources consumed when including the TX into a block. The sender of the TX pays for the fee in the native currency of the BC used. Such a fee protects the network from Denial-of-Service (DoS) attacks and provides incentives for TXs inclusion. BCs that support Smart Contracts (SC), thus, TXs can execute user-provided code, require a mechanism for fee calculation depending on the resources consumed by the code executed. Ethereum uses an elaborated mechanism compared to Bitcoin, leading to an increase in the attack surface of their SCs. The mechanism that makes the Bitcoin script - a limited version of SCs - more secure is the ability to compute, independent of the BC's state, an upperbound on resources needed to execute this TX. Thus, this work proposes a new approach enabling security benefits by defining an upper-bound on resource usage for general SCs. Furthermore, the approach allows for the payment of fees in any currency and not just the native currency of the BC.

A recent CSCML'2020 paper by Dolev and Liber presents a low cost blockchain based on cryptographic mechanism. Its main feature is a mechanism discouraging a user to fork a blockchain - if this happens, then a user's secret is leaked and thereby a proof of his misbehavior emerges. This approach is very attractive as long as we can guarantee that breaking the underlying cryptographic problem is infeasible for all parties. The situation changes dramatically in case of a partial compromise of a cryptographic scheme: when a powerful adversary can break the underlying scheme, while for the regular users the scheme is still resistant to attacks. In this case the blockchain techniques proposed becomes a dangerous trap allowing discrediting the users by powerful parties hiding own cryptanalytic power. To address this problem we introduce a David and Goliath adversary model, where a powerful adversary (Goliath) can break the underlying cryptographic assumption, but for a regular user (David) this is infeasible. For almost all cryptographic schemes, the situation of David is hopeless in this model: e.g., Goliath can forge standard signatures of David. Such an advantage of Goliath in case of a blockchain would be disastrous. We show that one can create a blockchain such that the advantage of Goliath is limited: if he creates a fork in a blockchain mimicking a double-spending attempt by David, then David can prove to be innocent.

Lightning Network is the most deployed Bitcoin-compatible Payment Channel Network (PCN), ensuring faster execution of transactions. However, this Layer-two solution has its fair share of problems. Topological analysis on Lightning Network reveals that Griefing Attack is a major problem whereby an adversary intentionally exhausts the channel capacity of the network. Though the attack does not always result in a direct monetary gain of the attacker, blocking of channel capacity for several days prevents several nodes from processing any future transaction request, leading to substantial collateral damage. If the attacker is able to lock funds in multiple paths simultaneously, then a major portion of the network may get stalled, reducing the throughput. Mitigating Griefing Attack still remains an open problem. In this paper, we propose an efficient countermeasure for the attack, known as Griefing-Penalty. To realize it, we propose a new payment protocol HTLC-GP or Hashed Timelock Contract with Griefing-Penalty. It not only preserves privacy but also ensures that an attacker cannot ascribe blame on any honest party present in the path relaying the payment. We evaluate the effectiveness of griefing-penalty using different attack strategies and test it on several snapshots of Lightning Network. Our evaluation results show that loss incurred is substantially high for HTLC-GP compared to HTLC.

Electronic money payment for public transportation uses cards or tags as the transaction media. The system is known as Check-In/Check-Out, which requires the owner of the card/tag to do an action of taking out the card to be scanned. This system has a deficiency in terms of time. Some of the existing public transportation systems can accommodate the passenger to obtain the location of the public transport itself, yet it is still unable to Figure the number of passengers that have already been inside the public transport. Therefore, this research’s purpose is to make a public transportation system that uses Bluetooth Low Energy based device as a transmitter which implements the Be-In/Be-Out System that will be carried by the passenger. As a result, it’s unessential for the passenger to do specific actions when riding public transport. They can also obtain the number of passengers inside public transport before riding it.

Smart contracts on the Ethereum blockchain are notoriously known as vulnerable to external attacks. Many of their issues led to a considerably large financial loss as they resulted from broken payments by digital assets, e.g., cryptocurrency. Existing research focused on specific patterns to find such problems, e.g., reentrancy bug, nondeterministic recipient etc., yet may lead to false alarms or miss important issues. To mitigate these limitations, we designed the SafePay analysis framework to find unfair payments in Ethereum smart contracts. Compared to existing analyzers, SafePay can detect potential blockchain transactions with feasible exploits thus effectively avoid false reports. Specifically, the detection is driven by a systematic search for violations on fair value exchange (FVE), i.e., a new security invariant introduced in SafePay to indicate that each party “fairly” pays to others. The preliminary evaluation validated the efficacy of SafePay by reporting previously unknown issues and decreasing the number of false alarms.

Blockchain is an emergent technology applied initially to cryptocurrencies, but with a much further reach. We present a secure, transaction-based system that handles motorized vehicle provenance (including ownership) over a distributed model using smart contracts on a blockchain. The system model includes the specification of various security protocols, verified using AVISPA-SPAN tool and guaranteeing privacy, authenticity, and other security features. A client of the system can have different roles accordingly to the relationship it has with the vehicle, and it can get various services and request transactions accordingly. Our proposal might contribute to reduce fraud and expand the applications of Blockchain.

The blockchain technology has been popular not only in cryptoassets but also in various fields of enterprise systems, where smart contracts between multiple stakeholders play a significant role. Hyperledger Fabric is one of the leading open-source enterprise blockchain platforms, which employs a unique consensus algorithm comprising three phases: endorsement, ordering, and committing. In this paper, three potential issues in Hyperledger Fabric are addressed when it is applied to enterprise systems: local alteration of ledgers, short of endorsers faced especially with private data, and auditing requirements. To solve and mitigate the issues, a blockchain verification tool bcverifier is proposed. This paper presents six requirements for the tool, the basic design of the tool, and how the design satisfies the requirements. It also clarifies the properties which the tool verifies in the ledger: immutability, consensus, and consistency in Hyperledger Fabric ledgers.

Public opinion is a public judgment regarding an event or a product. Traditional opinion data mining is often done to get conclusions about how influential an event or product is on society. In the current microblogging era, individual views of events and products can often be found in posts, such as Twitter. Based on the Twitter users’ habits, opinion data can be collected young using the crawling process of events or products. In the event of a pandemic, the use of e-money has increased quite drastically. The use of e-money simplifies the transaction process because everything can be processed only through a smart device. However, the increasing number of e-money users, especially during a pandemic, may not be in line with the increasing positive opinion of e-money. However, some may use e-money only out of necessity. We present classification performance results for the C4.5 decision tree and Naive Bayes classifiers. Lastly, we compare each classifier’s output using the voting-by-majority method to final predict positive or negative opinions about e-money in Indonesia. The proposed method can classify datasets from Twitter posts

In this paper, through the establishment of a vector model to confirm the relationship between electronic money and virtual economy, through the vector model we can see that the electronic money and virtual economy is proportional to. In addition, according to the model, we can see that the virtual economy will fluctuate greatly in the short term. Although there is a negative correction relationship between electronic money and virtual economy, there is a positive promotion relationship between electronic money and money supply. Under their joint action, when the fluctuation deviates from the short-term, the system will adjust automatically, making the fluctuation of the virtual economy more violent.

The recent popularization of distributed ledger technologies, which is better known in the financial sector due to digital currencies, has led to the appearance of numerous applications developed for the blockchain environment. The goal of this research is to investigate how a blockchain can contribute to the reduction of the vulnerabilities to corruption in the Brazilian context. Two stages of a literature review have been performed. The first identified the vulnerabilities to corruption in the Brazilian context and the second one identified the effective uses of blockchain characteristics. Subsequently, a deductive analysis was performed, aiming to verify which of the Blockchain initiatives presented could be potentially applied in the fight against corruption. This study points out ways to mitigate fraud and other causes of corruption to help regain society's trust in state institutions in Brazil, which has been suffering over the years from corruption scandals. Additionally, a research agenda leading to anti-corruption studies has been discussed.

Recent years have witnessed unprecedented growth in Mobile payments, digital wallet being the latest trend. These payments are very popular among young people in countries like China and India. In this paper we shall explore the extent of spread of digital payment, especially the digital wallet payments. In particular we shall study different aspects of digital payments in different region. Finally we shall look at the extent of these payments and associated technologies in the Kingdom of Saudi Arabia.

In recent years new financial services have emerged using technology as an intermediary media, one of which is e-money. Every year transactions using electronic money continue to increase. One of them is Bank Mandiri E-Money. In 2017, Bank Mandiri's E-Money became electronic money with the most ownership. As electronic money with the most ownership, Bank Mandiri E-Money is not immune from various problems. So, research is conducted regarding the evaluation of Bank Mandiri's E-Money usage, especially in Ciputat District. The purpose of this study was to evaluate the use of Bank Mandiri E-Money in Ciputat District and examine the variables of the UTAUT 2 model that influenced the use of Bank Mandiri E-Money in Ciputat District using a quantitative method with the PLS-SEM analysis technique approach. Determination of sampling in this study using a purposive sampling method with slovin formula calculation technique. Furthermore, recommendations can be made to Bank Mandiri for further development. For this reason, this research was conducted with a survey using a questionnaire on 127 Bank Mandiri E-Money users in the Ciputat District area. The results of this study show that of the 10 hypotheses tested, most of the hypotheses were accepted as many as 7 hypotheses and the ones rejected were 3 hypotheses. The Habit variable (HT) is the factor with the greatest influence and Effort Expectancy (EE) becomes the factor with the smallest influence. The benefits of this study are that it provides recommendations that related to model UTAUT 2 which can be used as material for consideration in the future development of Bank Mandiri E-Money.

Internet of Things (IoT) is an emerging technology that have been attracting significant attention from diverse application domains ranging from smart homes, smart cities to smart healthcare and manufacturing. Especially in smart city context, IoT devices play a significant role since the city of the future is an interconnected one, where distributed devices communicate with one another, constantly exchanging streams of real time data. However, the fundamental challenge on deploying such technology is the inherent limitations on IoT device’s computational power, network connectivity, energy consumption, which in turn hinders secure deployment. The introduction of Blockchain technology for digital cash offers a promising data security scheme for IoT applications in trust-less environments. Blockchain promises an elegant approach for secure information dissemination, machine-to-machine micro-transactions, and access control in a smart city context for IoT devices. However, the computational and storage requirements for original Blockchain model presents difficulties for IoT deployment. In this paper, we propose an experimental lightweight distributed ledger for IoT devices, TangoChain, utilizing a directed acyclic graph as underlying ledger data structure. We discuss the rationale behind our design approach, then present our in-progress proof-ofconcept prototype implementation details, and highlight the potentials for secure IoT device deployments in a smart city context.

This paper suggests a mathematical model of the electronic money payments' system, based on the graph analytics methods. This approach allows carrying out the system stability analysis on the base of crash-tests developed by authors. These crash-tests simulate the consecutive destruction of some central and peripheral nodes of graph (participants of electronic money payment system) due to both faults and failures of hardware and equipment and hacker attacks. The integral estimation of system stability is developed as a linear combination of graph few centrality measures ranked in a special order. The paper considers dynamics of graph centrality metrics and total metric during graph destruction and determines the critical level of destruction using a matrix for economic security

Electronic money based on servers, known as e-wallet, is a non-cash payment device. The number and amount of electronic money distributed in Indonesia has increased since the Gerakan Nasional Non Tunai (GNNT) launched by Bank Indonesia Governor on August 14, 2014. This study discussed factors influencing consumer behavioral intent to use in Indonesia's e-wallet adoption of Technology Acceptance Model (TAM), which is perceived as useful and user-friendly, as well as other variables of trust, enjoyment perception, feature, and m-payment experience. Data collection method used was quantitative method. Data were collected with questionnaires through google form provided that respondents have and have used GoPay, OVO and or DANA. The number of respondents were 343. Using the SmartPLS application, data were analyzed using the Structural Equation Modeling (SEM) method using Partial Least Square (PLS). The results showed that perceived enjoyment, m-payment experience and trust had a positive and significant influence on the behavioral intention to use in using e-wallet. Perceived ease of use also influenced trust and usefulness positively and significantly. Whereas the perceived ease of use and perceived usefulness had a positive but insignificant influence on behavioral intention to use, feature had a negative and insignificant influence on the behavioral intention to use in using the e-wallet.

In Ecuador, the need to introduce electronic money has been seen as a way to lighten the use of cash and renew the current financial system; however, this implementation has not yielded the desired result and instead has caused much more distrust on the part of Ecuadorians regarding the management of funds by the State; that is why this research show the use of a proprietary cryptocurrency as a new means of payment, in the Ecuadorian economy, leaving aside the current banking system and ensuring that any person, regardless of their income, can access this new financial transactional network . In order to adapt this system in the best way and according to the reality of the country, the theory behind the blockchain and, of course, the cryptocurrency has been studied, the legal environment currently in force in Ecuador, and it has been taken as a reference to Latin American countries that have already introduced these new means of payment in their financial system, analyzing their form of implementation, performance characteristics and results obtained in their economy.

It was determined a risk point in the payment model with electronic money, which is the time of the consumer's withdrawal and time of the provider's deposit. The problem is the damage caused to the information by the lack of a model to mitigate the risks to which the transactions of the payment system are exposed. The objective is to generate a prototype of a security model for the management of electronic money in Ecuador through the adoption of a cryptographic algorithm and improve the transactions security. It was used exploratory and deductive research as a method to analyze the reference information and the sequence of steps for the development of a prototype. It turned out a conceptual model of the participants in Ecuador; prototype electronic money security model; a prototype algorithm applied to the security of electronic money; a flow chart of the payment with electronic money; a mathematical formula to calculate the load of the model. It was concluded that the adoption of the AES algorithm in a security model for transactions generated in financial inclusion is robust and effective; this research has an alternative for the management of electronic money.

A blockchain is a distributed ledger in which participants that do not fully trust each other agree on the ledger's content by running a consensus algorithm. This technology is raising a lot of interest both in academia and industry, but the lack of tools to evaluate design and implementation decisions may hamper fast progress. To address this issue, this paper presents a discrete-event simulator that is flexible enough to evaluate different blockchain implementations. These blockchains can be rapidly modeled and simulated by extending existing models. Running Bitcoin and Ethereum simulations allowed us to change conditions and answer different questions about their performance. For example, we concluded that doubling the number of transactions per block has a low impact on the block propagation delay (10ms) and that encrypting communication has a high impact in that delay (more than 25%).

Blockchain-based cryptocurrencies have gained increasing adoption in recent years, and many hope that they may usher in a new era of decentralized electronic money. Unfortunately, they perform the core functions of money quite poorly due to their extremely volatile market value. On the other hand, blockchain “stablecoins” aiming to reduce this volatility, usually through a peg to an external currency like the US dollar, tend to greatly sacrifice decentralization of the money supply that make cryptocurrencies so attractive in the first place. Elasticoin is a novel currency issuance algorithm which greatly reduces price volatility by using the cryptographic puzzle of proofs of sequential work to fix the cost of minting a coin to sequential computation time. This causes coin supply to be highly elastic, quickly responding to demand for new coins and greatly dampening price swings. We argue that Elasticoin’s fixed-minting-cost approach to low volatility has significant advantages over using pegs or explicit measurement of demand to adjust supply.

The token economy is a form of decentralized digital economy with the support of blockchain. In the token economy, the responsibility, rights and interests in the real economy can be solidified on the blockchain to form true digital commitments with consensus, tamper-resistance, traceability and verification. These commitments can not only enhance the mutual trust between economic entities, but also realize the isomorphism of real economic activities and digital economic activities. Furthermore, they are conducive to improving the protection of property rights, strengthening the market’s allocation of resources, realizing the fair distribution of benefits, strengthening the government’s penetrating supervision, and creating a mutually beneficial business environment. Therefore, the token economy is expected to become a new form of digital economy with mutual trust and collective governance. To better illustrate the token economy, this paper introduces the concepts of blockchain, token and token economy, presents the reason why token economy could create a new form of digital economy with mutual trust and collective governance, and finally advances some suggestions on how to develop the token economy.

Payment transaction is now experiencing revolution as the rapid advancement of financial technology system. There is growing usage of e-money as a mean of payment in Indonesia. Besides, there is also a growing concern on the ethical aspect of e-money from an Islamic perspective, that is riba or usury. Previous studies have examined customers’ behavioral intention to use e-money by implementing Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM). However, none of them considering customers’ knowledge about riba that might become ethical aspect detaining them to use e-money as the mode of payment. The objective of this research is to examine the moderating effect of knowledge about riba on Technology Acceptance Model (TAM) variabels, such as perceived usefuleness, perceived ease of use and intention to use e-money. Data of this research are collected by distributing online questionnaires. By convenience sampling method, there are total 253 respondents. From the statistical computation, it is found that intention to use e-money is significantly affected by respondents’ perception of e-money usefulness and ease of use. Interestingly, it is also found that customers’ intention to use e-money are moderated by their knowledge about riba. Therefore, as managerial implication, it is suggested for e-money providers to build a Muslim-friendly system that is free from riba. Finally, this research also suggests future research agenda to consider subjective norm and religiosity variabels in a single model.

Food provenance is one of the most challenging problems that FSC. companies face today. A global supply chain network with multiple operating procedures and asymmetrical food regulations between countries makes end-to-end food tracking incidental to the food industry. Blockchain empowers new kinds of distributed applications design. Initially, Blockchain technology has been embraced in electronic money, yet this tech is significantly more promising for different areas loo. In this paper, are getting to present Blockchain technology easily. Additionally, we are talking that Blockchain technological innovation is also utilized in the industrial process from the retail industry to its advantage towards the client and additionally for that merchant to fantastic scope. During its heart, Blockchain is mainly thrilling because of the ability that it must empower increased confidence, transparency, and cooperation round constituencies which will otherwise battle to reach up to now belter. As distribution chain sophistication rises, there is an apparent chance to induce efficiency as a result of higher cooperation and transparency in between various constituencies like manufacturing companies, vendors and delivery carriers, insurance, importers, wholesalers, and merchants. Being aware of in Real-time the specific supply, spot, and condition of most inventory while in the machine might be quite a game-changer for most organizations, notably those working in perishable or luxury-goods. Unlike present systems, that rely heavily upon every element to keep its clear and dispersed database significance restricted and frequently postponed penetration to the standing of products anyplace from the machine Blockchain eases real-time and dependable information sharing one of the components and may provide consensus regarding the actual condition of their machine into parties.

Prior to blockchain technology coming into much usage, the earlier cryptographic digital cash schemes relied merely on trusted authorities. Bitcoin revolutionized this conventional view of a cryptocurrency, trading decentralized, distributed ledger, completely secured by the majority rule without predetermined authority or owner. Only standard cryptographic primitives such as signatures and hash functions were used to achieve security. Though other cryptocurrencies such as Bit-gold and B-money which are among the authority-free cryptocurrencies, Bitcoin is the first one to experience public acceptance on a large scale. There are various factors which contribute to Bitcoins success, though there is still a little question of doubt that the decentralized design of blockchain technology and perceived resilience to government or third-party intervention played an extremely crucial role in its uptake. Distributed crypto cash, more specifically in Blockchain technology has hailed as one key and most eminent and widely accepted innovation of Bitcoin. In this paper we have worked on the use of blockchain technology to implement cryptocurrency for IOT.

Blockchain is a decentralized ledger technology, and it is the technology underlying Bitcoin and Ethereum. The interest in blockchain has been increasing since its emergence. Hyperledger Fabric is one of the permissioned blockchain frameworks. One of the characteristics of Hyperledger Fabric is it utilizes general-purpose programming languages, e.g., Go, Node.js, and Java, to implement smart contracts (called chaincode in Hyperledger Fabric). The advantages of utilizing these languages are already known to potential developers, and development tools might already exist. However, one of the disadvantages is that these languages were not originally designed for writing smart contracts. Hence, there may be risks that developers do not need to consider when using specific languages such as Solidity of Ethereum. Furthermore, even though development tools exist, how many risks are covered by the tools is an open question. In this paper, we focus on Go language and the tools. First, we surveyed what kind of risks are associated with chaincodes are developed using Go language and observed there are 14 potential risks. Then, we investigated how many risks can be covered by Go tools, e.g., golint and gosec, and a vulnerability detection tool for chaincodes called Chaincode Scanner. From our results, we observed that some risks are not covered by the existing tools. Hence, we develop a detection tool to cover risks by static analysis. Finally, in this paper, we describe how to find the risks with our tool and evaluate the usefulness.

A cryptocurrency is a digital asset designed to work as a medium of exchange that uses cryptography to secure its transactions, to control the creation of additional units, and to verify the transfer of assets.Cryptocurrencies are a type of digital currencies, alternative currencies and virtual currencies. Cryptocurrencies use decentralized control as opposed to centralized electronic money and central banking systems. The decentralized control of each cryptocurrency works through a blockchain, which is a public transaction database, functioning as a distributed ledger.Neural Networks field has many techniques to perform predictions. They are widely used to predict the future values of stock exchange indicators variables. In this paper we will try to use Artificial Neural Network to predict cryptocurrencies close prices, and we’ll study the difference in price change with the normal stock exchanges.

In online payment, customers must transmit their personal and financial information through the website to conclude their purchase and pay the services or items selected. They may face possible fears from online transactions raised by their risk perception about financial or privacy loss. They may have concerns over the payment decision with the possible negative behaviors such as shopping cart abandonment. Therefore, customers have three major players that need to be addressed in online payment: the online seller, the payment page, and their own perception. However, few studies have explored these three players in an online purchasing environment. In this paper, we focus on the customer concerns and examine the antecedents of trust, payment security perception as well as their joint effect on two fundamentally important customers' aspects privacy concerns and financial fear perception. A total of 392 individuals participated in an online survey. The results highlight the importance, of the seller website's components (such as ease of use, security signs, and quality information) and their impact on the perceived payment security as well as their impact on customer's trust and financial fear perception. The objective of our study is to design a research model that explains the factors contributing to an online payment decision.

Distributed blockchain ledgers are on the verge of becoming a disruptive technology, profoundly impacting a wide range of industries and established applications, such as cryptocurrency, and allowing for novel use cases in both the public sector (e.g., eGovernment, eHealth, etc.) and the private sector (e.g., finance, supply chain management, etc.). Blockchains promise the ability to maintain critical information in a trustworthy repository without any centralized management. The reliability of blockchain-enabled applications is based on the innate immutability of stored data, maintained through cryptographic means, which enables blockchains to provide transparency, efficiency, auditability, trust, and security. As the technology is still in its infancy, a number of pain points must be addressed in order to make distributed ledgers more dependable, scalable, and pervasive. In this paper, we present the research landscape in distributed ledger technology (DLT). To do so, we describe a taxonomy of blockchain applications called blockchain generations. We also present the DCS properties (Decentralization, Consistency, and Scalability) as an analogy to the CAP theorem. Furthermore, we provide a general structure of the blockchain platform which decomposes the distributed ledger into six layers: Application, Modeling, Contract, System, Data, and Network. Finally, we classify research angles across three dimensions: DCS properties impacted, targeted applications, and related layers.

Business interest in blockchain technology is increasing due the potential for change that it offers. Large scale adoption in enterprise IT environments brings about a need for service management and DevOps processes for blockchain deployments. Nodes in the network may fail or be taken down for maintenance requiring visibility across hybrid, traditional, cloud enabled and cloud native deployments. Service management is necessary to ease deployment woes for those looking to install code within their own data centers on-premises or on dedicated cloud servers and further to handle the life cycle of the deployments that includes security patches, critical updates, upgrades, change management and restarting services. In this paper, we provide a mechanism to optimally perform such operations with no disruption to the consensus and transactions for such emerging blockchain applications.

As blockchain technologies mature and ecosystems over blockchain evolve, peers on blockchain networks often face situations in which they need to conduct voting for decision-making; as happened in the case of the DAO hard fork event on Ethereum. However, a natively built-in voting mechanism is not available on any of the existing blockchain platforms. Thus, the decision making either is delegated to a few network members who make such decisions offline or is dependent on third party online voting services. In both cases, peers directly or indirectly rely on trusted parties or centralized systems. This is against the basic decentralization principle of blockchain and exposes the election to frauds. To facilitate decision-making in a decentralized and secure manner, we propose a native blockchain voting protocol for peers to vote over their existing blockchain network without the need of any trusted or third party. Our protocol preserves end-to-end privacy and possesses desirable properties such as detectability and correctability against cheating. A reference implementation of our protocol on Hyperledger Fabric that demonstrates the validity and practical applicability of our protocol is also provided.

Proof-of-work was originally proposed by Dwork and Naor in 1992 and has proved its powerfulness in Bitcoin as a decentralized mechanism for blockchain construction. Proof-of-work is the basis of most popular cryptocurrencies and smart contract systems, where participating miners are required to solve difficult mathematical problems to validate transactions. One of the major challenges that proof-of-work faces is the 51% attack, i.e., if an adversary controls more than half of the computation power, he/she can control the blockchain construction and determine which blocks will be included. This is not a major concern when the number of miners is large. However, for an early stage blockchain system with a limited number of users, it is relatively easy for an attacker to launch the 51% attack. To mitigate such risk, we propose a new hybrid blockchain construction scheme that uses the combination of proof-of-work and the stake, which is the number of coins produced by a miner, to determine whether this miner is allowed to construct a block. We prove that stakes play an important role in the hybrid scheme at the beginning, so that an attacker is not able to launch the 51% attack even if he/she controls the majority of the computational power. Meanwhile, the hybrid scheme will converge to pure proof-of-work after sufficiently many blocks are generated, and thus captures the desired properties of proof-of-work. Most importantly, such a convergence is "smooth" in the sense that neither changes in the rules nor parameters are introduced, and thus no hard/soft-forks will be triggered. We also demonstrate the effectiveness of the new scheme using simulations with different configurations, which can help a designer to select adequate parameters for a specific blockchain application.

Bitcoin is a cryptocurrency based on blockchain technology that enables peer-to-peer transactions without a central authority. Bitcoin is known for resolving double-spending problems. When two or more miners generate a block that includes transaction information at nearly the same time, an accidental fork occurs. In this case, the longest chain of blocks is selected to avoid the double-spending problem. However, if there is an attacker node whose hash power is greater than half of the total hash power, that node can perform a double-spending attack, i.e., a 51% or majority attack. We propose a random mining group selection technique to reduce the probability of successful double-spending attacks. The analysis results demonstrate that if the number of groups is greater than or equal to two, the probability that the attacker will find the next block is less than 50%.

Bitcoin is a decentralized transaction platform and the largest cryptocurrency system. Bitcoin represents a chain of blocks containing its entire legal transaction history, thereby providing convenience for tracking money. However, mixing services are used as an effective means to hide the identity of a transaction address by combining several transfers from different users. Detecting the original user of a Bitcoin address and the money flow is essential in some special circumstances such as anomaly detection. Recognizing Bitcoin mixing services and de-mixing user accounts have only rarely been studied. Here we demonstrate that Bitcoin transaction graphs possess community properties and that a mixing service can be regarded as a cluster outlier. Motivated by the success of graph embedding in social network analysis, we propose a feature-based method to identify mixing services, testing our method on the real Bitcoin ledger.

Offline electronic cash systems, an attractive payment platform for electronic commerce, enable customers to pay his electronic money in business transactions via the Internet. In 2013, Baseri et al. proposed an offline electronic cash (e-cash) system using RSA cryptosystem and asserted that their system satisfied anonymity, double spending detection, unforgeability, and date attachability properties and prevented forging. However, we find that their e-cash system is insecure against identity forgery. In this paper, we show that an adversary has three ways to forge a valid identity to withdraw electronic coin (e-coin) from his account at the bank and pay it to the merchant in payment phase. When double spending is detected, the bank cannot reveal the attacker's real identity.