Store Transaction Research Articles

Blockchain-Based Reliable Traceability System for Telecom Big Data Transactions

Telecom big data generated by telecom networks have a high economic value. Thus, telecom operators actively explore telecom big data transactions methods to minimize the possibility of leaking users’ privacy. The existing solutions do not allow the data sets to leave the database, instead only allow the buyers to send data mining algorithms to the telecom operator’s platform for training. However, this centralized platform has a high risk of tampering. In addition, the currently existing solutions cannot be used to accurately and quickly trace the information of telecom big data transactions. To address these limitations, we propose a blockchain-based reliable traceability system for telecom big data transactions using smart contracts and the InterPlanetary File System. Two types of smart contracts are developed to store transaction information for tracing. Access control strategies and a reapproval prevention strategy are designed for ensuring the safe operation of the system and avoiding the problem of favoritism and fraud. We use Ethereum as a verification platform to develop and evaluate this system. The implementation of functions, such as purchasing data sets, sending algorithms, obtaining results, and tracing transactions in the smart contract and the implementation of the proposed strategies are verified. The results demonstrate that the performance of the proposed system is better than the existing solutions, and the traceability response time is improved to the order of seconds, so as to realize the safe and efficient traceability of telecom big data transactions. In addition, Ethereum and Hyperledger Fabric v0.6 were discussed to provide insights for future development.

TEMPLATE-BASED MODEL FOR SHORT-TERM FORECASTING OF THE NUMBER OF TRANSACTIONS IN RETAIL CLOTHING STORES

Obtaining predictive values of indicators based on historical data represented by time series plays a crucial role in making business decisions in various industries. One of these areas of application is the task of predicting the number of transactions in retail stores in order to optimally plan the working hours of employees and achieve maximum customer satisfaction with the quality of service. The choice of an appropriate time series forecasting model depends on the forecast horizon, as well as the characteristics of the time series, namely trend, seasonality, cyclicality, and irregularity. Traditional time series analysis and forecasting methods are designed to handle a single seasonality in a time series, but in the presence of multiple seasonality, these methods do not work satisfactorily. The use of time series decomposition methods is characterized by computational complexity. The use of machine learning methods is also not always advisable for a number of different reasons. Thus, it is necessary to use simple adaptive models, based on selected patterns, for recurring seasonal data of complex structure. The main goal of this article is to develop a successful adaptive model and propose methods for using it for short-term forecasting of the number of transactions based on time series data. For estimation purposes, a set of hourly time series of the number of customers (transactions) of some retail chain stores, characterized by multiple seasonality, is used. The results of computational experiments show that the proposed template-based model is quite effective for obtaining short-term predictive values. This model, characterized by simplicity, intuitiveness and a minimum number of tuning parameters, can actually be applied to any area of data represented by time series.

Web Application Development for Syari Online Shop Using 4D Model Development

: Haransaf shop is a shop that sells clothes and all Muslim/Muslim knick-knacks. Depending results of observations and data searches directly to the field with increasing requests. The use of technology in data processing of Haransaf Online Store Transactions has not been effective and efficient so that reporting takes a long time. The recording of the Haransaf store report still uses a manual system, which is still written on notes and then recorded in the sales book. The focus of this research is on an attractive interface, ease of use, and delivery of product information to consumers by utilizing the website as an online service. The research method uses 4-D. The model in the development of an online store must use a 4D model. The 4D model has four stages, namely Define, Design, Develop and Disseminate. The website-based Haransaf Online Store that uses the Codeigniter 4 Framework, functions well to produce a sales management system that manages the Haransaf online store. With the existence of this online store, it is hoped that it can provide an increase in revenue at the Haransaf Store and benefits in the form of a wider scope.

Blockchain: The Gateway to New Technology and its Applications for Academic Libraries

The block chain is a distributed database that stores and shares records of all transactions or digital events that have taken place. Each transaction is double-checked by the majority of the system's members. It holds every single transaction's record. The block chain is a novel technology that is being used to validate and store transaction records for online crypto currencies such as Bit coin. Transactions cannot be retracted, copied, or faked because the system is redundant and distributed. The block chain has potential applications in domains other than online money, such as public libraries. This column will briefly outline what a block chain is and how it is used, as well as potential future uses that librarians and Academic Library practitioners would be interested in, as well as some of the system's flaws. Information workers may be able to utilize and benefit from this technology in a variety of ways.

The impact of the COVID-19 pandemic on grocery shopper behaviour: Analysis of shopper behaviour change using store transaction data.

The systemic shock of coronavirus (COVID‐19) and its impact on the global economy has been unprecedented with grocery shopper behaviour changing dramatically through various stages of the pandemic. COVID‐19 has caused unusual market conditions, with significant changes to grocery shopper behaviour that need to be understood to allow for appreciation of shopper behaviour change and retail planning implications during future systemic shocks. The aim of this study was therefore to understand grocery‐shopping behaviour during COVID‐19. Specific objectives were to investigate changes to grocery sale patterns by basket size, composition and category, as well as during specific time periods of the pandemic. The use of transaction data using a range of market basket indicators (e.g., value, size, product mix), revealed profound changes that indicate the challenge shoppers faced navigating a new ‘normal grocery shop’ and the pressure on retailers to analyse consumption changes in order to prioritise demand planning. While the use of this data and analysis approach is an important contribution to consumer behaviour research, our focus was on the bigger patterns observed through the data pertaining to changes in shopper behaviour during systemic shocks. A key contribution of this paper is how the use of transaction data from grocery retail provides a nuanced understanding of how grocery shoppers responded leading up to and during the pandemic. For example, we found that grocery shoppers purchased more than just ‘daily staples’ to stock‐up during the pandemic, with increased awareness of health and wellbeing an important aspect.

Towards self-stabilizing blockchain, reconstructing totally erased blockchain

Blockchains are commonly used for crypto-currency systems, where they publicly store transactions. In a permissioned blockchain, only a few participants (nodes) can push new transactions to the chain. The known boundary on the number of faulty participants – up to f for 3f+1 participants – may be surpassed, causing the underlying consensus algorithm (BFT) to fail. When a malicious adversary compromises or corrupts enough nodes it may lead to the complete corruption of the ledger and even to the destruction of ledger copies the nodes hold. We suggest a reconstruction solution for the blockchain in the event of such an attack. We present a technique using verifiable secret sharing (VSS), making our solution immediate, requires no trust between the different blockchain parties, and provides each user an independent reconstruction. Our solution enables the exposure of an end-user's private key in case of dishonest reconstruction, thus, removing the incentive of such an act.

ПОСТКВАНТОВЫЕ АЛГОРИТМЫ ЭЛЕКТРОННОЙ ЦИФРОВОЙ ПОДПИСИ И ИХ ИСПОЛЬЗОВАНИЕ В РАСПРЕДЕЛЕННОМ РЕЕСТРЕ

Introduction: The creation of systems based on blockchain technology is a promising area of modern research and development. Blockchain is a reliable and secure way to store transaction data, providing integrity verification capabilities. Today, blockchain technology is widely spread all over the world, in many spheres of life. The article considers the essence and characteristics of post quantum electronic signature algorithms based on algebraic lattices and provides a comparative analysis of algorithms by conditional and unconditional criteria. Results. The advantages and disadvantages of existing cryptographic algorithms, the principles and specifics of the functioning of blockchain technology, as well as the possibility of using post quantum algorithms in the formation of block signatures are determined.

Coding for Scalable Blockchains via Dynamic Distributed Storage

Blockchains store transaction data in the form of a distributed ledger where each node in the network stores a current copy of the sequence of transactions as a hash chain. This requirement of storing the entire ledger incurs a high storage cost that grows undesirably large for high transaction rates and large networks. In this work we use secret key sharing, private key encryption, and distributed storage to design a coding scheme such that each node stores only a part of each transaction, thereby reducing the cold storage cost to a fraction of its original cost. In addition, the storage code ensures the security of the storage from active adversaries that may aim to corrupt prior transactions by altering copies of the ledger. We further employ a dynamic zone allocation algorithm that spreads the node allocation and data distribution across transactions. Under this coding scheme we show that we can also improve the integrity of the transaction data in the network over current schemes.

Blockchain-based federated learning methodologies in smart environments.

Blockchain technology is an undeniable ledger technology that stores transactions in high-security chains of blocks. Blockchain can solve security and privacy issues in a variety of domains. With the rapid development of smart environments and complicated contracts between users and intelligent devices, federated learning (FL) is a new paradigm to improve accuracy and precision factors of data mining by supporting information privacy and security. Much sensitive information such as patient health records, safety industrial information, and banking personal information in various domains of the Internet of Things (IoT) including smart city, smart healthcare, and smart industry should be collected and gathered to train and test with high potential privacy and secured manner. Using blockchain technology to the adaption of intelligent learning can influence maintaining and sustaining information security and privacy. Finally, blockchain-based FL mechanisms are very hot topics and cut of scientific edge in data science and artificial intelligence. This research proposes a systematic study on the discussion of privacy and security in the field of blockchain-based FL methodologies on the scientific databases to provide an objective road map of the status of this issue. According to the analytical results of this research, blockchain-based FL has been grown significantly during these 5 years and blockchain technology has been used more to solve problems related to patient healthcare records, image retrieval, cancer datasets, industrial equipment, and economical information in the field of IoT applications and smart environments.

The Design of Case-involved Property Transfer System Based on Blockchain

In recent years, with the continuous maturity of blockchain technology, more and more applications based on blockchain appear in our life. The safe sharing and rapid disposal of caseinvolved property information is the focus of online case management. At present, due to some characteristics of case-involved properties, the case platform with centralized management has some issues, such as low collaborative efficiency and low intelligence. In this paper, we propose the architecture and implementation scheme of the cross departmental case-involved property transfer system based on blockchain. By introducing the blockchain technology, we have established a multi departmental case-involved property information transfer alliance chain across the public security, procuratorial and judicial departments. The case-involved property transfer system uses smart contract to implement a set of case-involved property transfer procedures designed by our investigation and research. It proposes an infrastructure of alliance blockchain based on multi-chain technology according to the business logic and makes the public security, procuratorial and judicial departments as the alliance blockchain nodes. Blockchain technology can make all nodes store transaction data. So it can efficiently realize the sharing of case-involved property information, leave traces in transaction processing and trace the processing source of case-involved properties.

Performance Analysis of the IOTA DAG-Based Distributed Ledger

Distributed ledgers (DLs) provide many advantages over centralized solutions in Internet of Things projects, including but not limited to improved security, transparency, and fault tolerance. To leverage DLs at scale, their well-known limitation (i.e., performance) should be adequately analyzed and addressed. Directed acyclic graph-based DLs have been proposed to tackle the performance and scalability issues by design. The first among them, IOTA, has shown promising signs in addressing the preceding issues. IOTA is an open source DL designed for the Internet of Things. It uses a directed acyclic graph to store transactions on its ledger, to achieve a potentially higher scalability over blockchain-based DLs. However, due to the uncertainty and centralization of the deployed consensus, the current IOTA implementation exposes some performance issues, making it less performant than the initial design. In this article, we first extend an existing simulator to support realistic IOTA simulations and investigate the impact of different design parameters on IOTA’s performance. Then, we propose a layered model to help the users of IOTA determine the optimal waiting time to resend the previously submitted but not yet confirmed transaction. Our findings reveal the impact of the transaction arrival rate, tip selection algorithms, weighted tip selection algorithm randomness, and network delay on the throughput. Using the proposed layered model, we shed some light on the distribution of the confirmed transactions. The distribution is leveraged to calculate the optimal time for resending an unconfirmed transaction to the DL. The performance analysis results can be used by both system designers and users to support their decision making.

Web and Application Program Interface (API) Design “Parmon” Modern Parking Application

Samarinda city is one of the cities with large local revenue potential in the large parking fee sector. This is evidenced by the quite fast increasing number of users of two-wheeled and four-wheeled vehicles. But due to the increase in vehicle users in Samarinda it has not had a significant impact on the parking fee sector. This is because there is no clear record of every parking transaction. In this case the parking lot is open or roadside. The collection of parking fees in Samarinda there are still many obstacles faced by UTPD parking management, there are still many illegal parking spaces managed by irresponsible elements. One technology that is currently quite developed is the web. With the web, all data and information can be distributed effectively and efficiently and contain and display various information that can be accessed by various devices. Based on the problems and technological developments that have been presented, an idea emerged about the need to create a web-based information system to store and record transactions at any time and create an API for supporting applications. It is expected from this study that every transaction for drivers and drivers can be recorded so that the government can clearly know the income and the amount of levy tax from parking that must be paid by each parking attendant in the “Parmon” application.

Efficient Local Secret Sharing for Distributed Blockchain Systems

Blockchain system store transaction data in the form of a distributed database where each peer is to maintain an identical copy. Blockchain systems resemble repetition codes, incurring high storage cost. Recently, distributed storage blockchain (DSB) systems have been proposed to improve storage efficiency by incorporating secret sharing, private key encryption, and information dispersal algorithms. However, the DSB results in significant communication cost when peer failures occur due to denial of service attacks. In this project, we propose a new DSB approach based on a local secret sharing (LSS) scheme with a hierarchical secret structure of one global secret node and several local secret nodes. The proposed DSB approach with LSS improves the storage and recovery communication costs.

Consumer valuation of blockchain traceability for beef in the United States

AbstractBlockchain (BC) technology, defined as a shared information system to validate, secure, and permanently store transactions among multiple parties on a distributed ledger, presents many applications in agricultural and food industries. This study examines the application of BC in food traceability for beef in the United States using a choice experiment. Findings indicate that consumers value USDA certifications over BC traceability to guide their meat preferences. Our study suggests a number of industry implications, the most important of which suggests focusing business and consumer education on the value of product data, rather than on the value of the technologies that manage data.

Threshold-Based Post-Quantum Secure Verifiable Multi-Secret Sharing for Distributed Storage Blockchain

Blockchain systems store transaction data in the form of a distributed ledger where each node stores a copy of all data, which gives rise to storage issues. It is well-known that the tremendous storage and distribution of the block data are common problems in blockchain systems. In the literature, some types of secret sharing schemes are employed to overcome these problems. The secret sharing method is one of the most significant cryptographic protocols used to ensure the privacy of the data. The main purpose of this paper is to improve the recent distributed storage blockchain systems by proposing an alternative secret sharing method. We first propose a secure threshold verifiable multi-secret sharing scheme that has the verification and private communication steps based on post-quantum lattice-based hard problems. We then apply the proposed threshold scheme to the distributed storage blockchain (DSB) system to share transaction data at each block. In the proposed DSB system, we encrypt the data block with the AES-256 encryption algorithm before distributing it among nodes at each block, and both its secret key and the hash value of the block are privately shared among nodes simultaneously by the proposed scheme. Thereafter, in the DSB system, the encrypted data block is encoded by the Reed–Solomon code, and it is shared among nodes. We finally analyze the storage and recovery communication costs and the robustness of the proposed DSB system. We observe that our approach improves effectively the recovery communication cost and makes it more robust compared to the previous DSB systems. It also improves extremely the storage cost of the traditional blockchain systems. Furthermore, the proposed scheme brings to the DSB system the desirable properties such as verification process and secret communication without private channels in addition to the known properties of the schemes used in the previous DSB systems. As a result of the flexibility on the threshold parameter of the scheme, a diverse range of qualified subsets of nodes in the DSB system can privately recover the secret values.

Product recommendation system on building materials shopping using FP-Growth algorithm

The application program created is an e-commerce website based application program that is used to provide product choices for building materials using the FP- Growth algorithm. This algorithm is used to find frequent itemset (data that most often appears) on store transaction data from January 2019 to the most recent transaction. The use of FP-Tree which is used simultaneously with the FP-Growth algorithm only scans the database 2 times. The first scanning is done to read the previous store sales transaction data. The second scanning on the tree trace to form a pattern. After obtaining a number of linkages that are higher than the minimum support from the transaction data, product choices can be generated on the website. This application was created using the Hypertext Processor (PHP) programming language base which is supported by the MySQL database and SQL Server. It is expected that the presence of web-based applications can improve store sales and the marketing process of building products for the better.

‘E-commerce’ for India in a Developing World: An Int’l Trade Law Perspective

Ever since internet has stepped in the domain of markets, the style of conducting commercial transactions has changed. E-Commerce transactions are very different from the everyday buying at the store transactions and they are gaining more significance by the day. Due to the everevolving technology driven nature of these e-markets, regulators across the globe are exploring ways to discipline them without causing much distortions. However, the job is more complicated than it appears. In these circumstances, while India is in the phase of drafting its National ECommerce Policy, its international forefront reflects carefulness in engaging in the ongoing negotiations. This article aims to explore the complexity of e-commerce from the international trade forefront and its implications for developing countries like India. International Trade, Electronic Commerce, E-Commerce, Regulation, Developing Countries, Role of Regulators, Competition, Digital Trade.

Testing the Effectiveness of Enhanced Alcohol Warning Labels and Modifications Resulting From Alcohol Industry Interference in Yukon, Canada: Protocol for a Quasi-Experimental Study.

BackgroundAlcohol warning labels are a promising, well-targeted strategy to increase public awareness of alcohol-related health risks and support more informed and safer use. However, evidence of their effectiveness in real-world settings remains limited and inconclusive.ObjectiveThis paper presents a protocol for a real-world study examining the population-level impact of enhanced alcohol warning labels with a cancer message; national drinking guidelines; and standard drink information on attention, processing, and alcohol-related behaviors among consumers in Canada. Postimplementation modifications to the original protocol due to interference by national alcohol industry representatives are also described.MethodsThis quasi-experimental study involved partnering with local governments in two northern Canadian territories already applying alcohol warning labels on alcohol containers for sale in liquor stores. The study tested an 8-month intervention consisting of three new enhanced, rotating alcohol warning labels in an intervention site (Whitehorse, Yukon) relative to a comparison site (Yellowknife, Northwest Territories) where labelling practices would remain unchanged. Pre-post surveys were conducted at both sites to measure changes in awareness and processing of label messages, alcohol-related knowledge, and behaviors. Liquor store transaction data were collected from both sites to assess changes in population-level alcohol consumption. The intervention was successfully implemented for 1 month before it was halted due to complaints from the alcohol industry. The government of the intervention site allowed the study to proceed after a 2-month pause, on the condition that the cancer warning label was removed from rotation. Modifications to the protocol included applying the two remaining enhanced labels for the balance of the intervention and adding a third wave of surveys during the 2-month pause to capture any impact of the cancer label.ResultsThis study protocol describes a real-world quasi-experimental study that aimed to test the effectiveness of new enhanced alcohol warning labels as a tool to support consumers in making more informed and safer alcohol choices. Alcohol industry interference shortly after implementation compromised both the intervention and the original study design; however, the study design was modified to enable completion of three waves of surveys with cohort participants (n=2049) and meet the study aims.ConclusionsFindings from this study will directly inform alcohol labelling policies in Canada and internationally and provide further insight into the alcohol industry’s attempts to disrupt research in this area. Additional unimpeded real-world evaluations of enhanced alcohol warning labels are recommended.International Registered Report Identifier (IRRID)RR1-10.2196/16320

PERANCANGAN APLIKASI E-COMMERCE DENGAN METODE COLLABORATIVE FILTERING DAN APRIORI

This e-Commerce application is an application for Rajawali Electric Store. This application is made using Collaborative Filtering and Apriori method to recommend products from Rajawali Electric Store. This Application will give product recommendations based on user transactions and user rating. Transaction data used in Apriori method were taken from Rajawali Electric store transaction data, while rating data in Collaborative Filtering method were taken from several websites that have product rating. Results from Apriori method shows that with 50% support value, user that buys Recessed White 66664 and Bulb 19w CDL E27 A80 have the possibility of buying Bulb 14.5W E27 220-240V A67 with confidence value of 89.47%. Results from Collaborative Method produced different results based on users and types of products

Hybridchain: A Novel Architecture for Confidentiality-Preserving and Performant Permissioned Blockchain Using Trusted Execution Environment

Blockchain is making headlines due to it promises to provide a decentralized, transparent, tamper-resistant, traceable and verifiable historical transaction records that can resist faults of any single node. According to the latest data from State of the Dapps, developers have currently released 3,717 Decentralized Applications (DApps), only three have an average of more than 10,000 daily active users. Most of the real-world DApps exercise little of their potential power. The key reason is that the current permissioned blockchain systems suffer from poor performance and lack of confidentiality. To address this issue, we present Hybridchain, a system that combines blockchain with Trusted Execution Environment (TEE). Hybridchain decouples computation from consensus and adopts hierarchical network to minimize the computational burden and latency of on-chain execution by performing most of the heavy-weight computation off-chain. Hybridchain leverages secure communication protocols to enable each participant to share transaction data in a secure way. To mitigate the small enclave memory restriction of TEE, Hybridchain extends the enclave memory that allows blockchain applications running in TEE to securely store transaction records to the whole key-value storage codes placed outside of TEE. Analysis and experiments of sealed-bid auction show that Hybridchain can support confidentiality-preserving along with high performance.