Karar bilimi karar verme işini kolaylaştırmak ve geliştirmek için eldeki sınırlı bilgiyi kullanarak pek çok teknikten faydalanır. Bu nedenle ekonomi, istatistik, üretim yönetimi ve kontrolü ve psikoloji gibi bilim dallarını da içeren disiplinler arası bir alandır. Sürekli olarak karşı karşıya kalınan karar verme durumu neticesinde verilen kararlar ve sonrasında atılan adımlar ise geleceği şekillendirmektedir. Bu nedenle karar biliminin günümüzdeki yeri oldukça önemlidir. Bu çalışmada 2012-2021 yılları içerisinde karar bilimi alanında üretilen bilimsel çıktıların değerlendirilmesi amaçlanmaktadır. Bu amaçla Scopus/SciVal veri tabanı üzerinden ulaşılan 508.220 bilimsel çıktı incelenmiş, yıllara göre bilimsel çıktı sayısı, atıf sayısı, görüntülenme sayısı bilgileri paylaşılmıştır. Dünya genelinde üretilen bilimsel çıktıları kapsayan bu çalışmada karar bilimi alanında en fazla bilimsel çıktının 2021 yılında (95.109) üretildiği ve en fazla bilimsel çıktıya sahip ülkenin Çin (106.752) olduğu sonucuna ulaşılmıştır. Ayrıca en fazla bilimsel çıktıya sahip enstitü/üniversitenin CNRS (10.411) ve en fazla bilimsel çıktıya yer veren derginin “IFIP Advances in Information and Communication Technology” (10.084) olduğu belirlenmiştir. Bilimsel çıktı sayısı dikkate alındığında yapılan çalışmalarda daha çok kurumsal işbirliklerinin tercih edildiği (201.933) ve karar bilimi alanı içerisinde en fazla çalışılan konuların “Bitcoin; Ethereum; Nesnelerin İnterneti” (16473) olduğu sonucuna ulaşılmıştır. Genel olarak yapılan bu çalışma karar bilimi alanında çalışan araştırmacılar için bilgilendirme, değerlendirme ve yönlendirme özelliklerini taşımaktadır.
Purpose This paper aims to study the interlinkages between cryptocurrency and the stock market by characterizing their connectedness and the effects of the COVID-19 crisis on their relations. Design/methodology/approach The author employs a quantile vector autoregression (QVAR) to identify the connectedness of nine indicators from January 1, 2018, to December 31, 2021, in an effort to examine the relationships between cryptocurrency and stock markets. Findings The results demonstrate that the pandemic shocks appear to have influences on the system-wide dynamic connectedness. Dynamic net total directional connectedness implies that Bitcoin (BTC) is a net short-duration shock transmitter during the sample. BTC is a long-duration net receiver of shocks during the 2018–2020 period and turns into a long-duration net transmitter of shocks in late 2021. Ethereum is a net shock transmitter in both durations. Binance turns into a net short-duration shock transmitter during the COVID-19 outbreak before receiving net shocks in 2021. The stock market in different areas plays various roles in the short run and long run. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the most severe impact at the beginning of 2020. Practical implications Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets. Originality/value The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages between these two markets.
Ethereum Trader is a crypto exchanging programming made to mechanize the trading of digital currencies. The exchanging framework utilizes Man-made brainpower (computer based intelligence) and AI (ML) calculations to recognize possibly beneficial exchanging open doors and execute them continuously. As per the data gave on the site, <strong>Ethereum Trader</strong> has an exchanging arrangement that is both exceptionally viable and speedy. It is stacked with different highlights intended to make life more straightforward for shoppers. https://www.theethereumtrader.com/
As the Blockchain technology develops, more and more cryptocurrencies were invented after Bitcoin. This paper introduces the technology of Blockchain, including the basic concept of Blockchain and how Blockchain works to allow decentralization of trades; The system of Ethereum and the cryptocurrency Ether (ETH), how it was invented, what was the central mission of its invention, as well as how it differs from Bitcoin and how can it allow more decentralized application to be developed, which in turn illustrates what it means and where its values lie. As all cryptocurrency markets have a huge fall in value in the year 2022, as shown in figure 1, many people are losing faith in cryptocurrency. Many believe that since it is entirely digital and non-government based, it has no actual value, that the entire cryptocurrency market is a bubble. Meanwhile, cryptocurrencies introduce a very revolutionary concept, which is the decentralization of applications, and this decentralization can apply to many things, leading to a great technological structure modification, even for social structures. Because of its anonymous and democratic nature, there is also always going to be demand for cryptocurrencies. Thus, this paper also analyzes the expectations of cryptocurrency, mainly Ether, and the predictions of its future development.
Prof. M. S. Kale, Ayush Gimekar, Zuveriya Tamboli, Vaishnavi Patil · 5 authors
Normal cash has developed and appears numerous downsides such as inaccessibility. It is inclined to burglary and is intensely directed by government offices. Cryptocurrencies have risen as a egotistic money related framework. They depend upon secure disseminated ledger data structure. Mining plays a critical portion in this framework. Basically, our cryptocurrency could be a conveyed database that keeps up tamper-proof information structure pieces containing his bunches of person exchanges. Blockchain innovation can be a widely emerging approach to data innovations. Bitcoin as a cryptocurrency has made several considerations since it was one of its earliest implementations. They discuss the key elements driving the development of sophisticated cryptocurrencies alongside Ethereum, a blockchain implementation with a focus on informed contracts. In its most basic form, our cryptocurrency may be thought of as a distributed database that keeps track of tamper-proof data structure blocks comprising batches of individual transactions.
Anurag Dutta, Liton Chandra Voumik, A. Ramamoorthy, Samrat Ray · 5 authors
Cryptocurrencies are in high demand now due to their volatile and untraceable nature. Bitcoin, Ethereum, and Dogecoin are just a few examples. This research seeks to identify deception and probable fraud in Ethereum transactional processes. We have developed this capability via ChaosNet, an Artificial Neural Network constructed using Generalized Luröth Series maps. Chaos has been objectively discovered in the brain at many spatiotemporal scales. Several synthetic neuronal simulations, including the Hindmarsh–Rose model, possess chaos, and individual brain neurons are known to display chaotic bursting phenomena. Although chaos is included in several Artificial Neural Networks (ANNs), for instance, in Recursively Generating Neural Networks, no ANNs exist for classical tasks entirely made up of chaoticity. ChaosNet uses the chaotic GLS neurons’ property of topological transitivity to perform classification problems on pools of data with cutting-edge performance, lowering the necessary training sample count. This synthetic neural network can perform categorization tasks by gathering a definite amount of training data. ChaosNet utilizes some of the best traits of networks composed of biological neurons, which derive from the strong chaotic activity of individual neurons, to solve complex classification tasks on par with or better than standard Artificial Neural Networks. It has been shown to require much fewer training samples. This ability of ChaosNet has been well exploited for the objective of our research. Further, in this article, ChaosNet has been integrated with several well-known ML algorithms to cater to the purposes of this study. The results obtained are better than the generic results.
As various forms of fraud proliferate on Ethereum, it is imperative to safeguard against these malicious activities to protect susceptible users from being victimized. While current studies solely rely on graph-based fraud detection approaches, it is argued that they may not be well-suited for dealing with highly repetitive, skew-distributed and heterogeneous Ethereum transactions. To address these challenges, we propose BERT4ETH, a universal pre-trained Transformer encoder that serves as an account representation extractor for detecting various fraud behaviors on Ethereum. BERT4ETH features the superior modeling capability of Transformer to capture the dynamic sequential patterns inherent in Ethereum transactions, and addresses the challenges of pre-training a BERT model for Ethereum with three practical and effective strategies, namely repetitiveness reduction, skew alleviation and heterogeneity modeling. Our empirical evaluation demonstrates that BERT4ETH outperforms state-of-the-art methods with significant enhancements in terms of the phishing account detection and de-anonymization tasks. The code for BERT4ETH is available at: https://github.com/git-disl/BERT4ETH.
<strong>Purpose: </strong><em>With the emergence of Online Purchasing, Product Identification is an essential model that allows the seller to add a product to a decentralized platform such as Blockchain and allows buyers to purchase the product from the decentralized platform. Fraud products, counterfeiting, and duplication are the current marketplace's major problems. This aims to develop a system for verifying product identification with their information, ownership, and validity detail.</em> <strong>Design/Methodology/Approach: </strong><em>The proposed system applies Extreme Programming (XP) to reduce the risk caused by the fixed-time project using new technology and thus the final project could be delivered in time. Solidity and metamask being new technologies were unstable and to adopt the changes, the agile development model was the best through ABI and the bytecode are deployed into the Ethereum Blockchain.</em> <strong>Findings/Result: </strong><em>This system maintains the buyers, sellers, and product details in a decentralized blockchain platform. This research details the entire product development process from planning, analysis, design, implementation, and testing for systematic online purchasing. Verifying the product ownership and its information to get the original product is the major difficulty in this space, but this research systematically solves some of those problems. This signifies an improvement in the current centralized way of purchasing goods online, where the information remains as it is entered by the seller while listing the product in Nepal and developing countries context.</em> <strong>Originality/Value: </strong><em>The study has produced a decentralized, reliable, secure, and third-party independent marketplace for buying and selling products for fraud free market.</em> <strong>Paper Type: </strong><em>Research paper</em>
This study examines the time-varying connectedness among the realized volatilities of seven major cryptocurrencies between January 2020 and May 2022. To this end, we implement the time and frequency connectedness time-varying parameter vector autoregression (TVP-VAR) approaches. Our findings propose that (i) the COVID-19 pandemic significantly affected the dynamic connectedness; (ii) the total connectedness index hits its apex around the official announcement of the pandemic; (iii) in line with previous studies Ethereum, Bitcoin, and Link are the largest propagators/recipients of shocks; (iv) the tightest volatility interdependencies are related to the short-run.
As the largest blockchain platform that supports smart contracts, Ethereum has developed with an incredible speed. Yet due to the anonymity of blockchain, the popularity of Ethereum has fostered the emergence of various illegal activities and money laundering by converting ill-gotten funds to cash. In the traditional money laundering scenario, researchers have uncovered the prevalent traits of money laundering. However, since money laundering on Ethereum is an emerging means, little is known about money laundering on Ethereum. To fill the gap, in this paper, we conduct an in-depth study on Ethereum money laundering networks through the lens of a representative security event on \textit{Upbit Exchange} to explore whether money laundering on Ethereum has traditional traits. Specifically, we construct a money laundering network on Ethereum by crawling the transaction records of \textit{Upbit Hack}. Then, we present five questions based on the traditional traits of money laundering networks. By leveraging network analysis, we characterize the money laundering network on Ethereum and answer these questions. In the end, we summarize the findings of money laundering networks on Ethereum, which lay the groundwork for money laundering detection on Ethereum.
<p>The study analysed the importance of blockchain transaction features to identify suspicious activities. The feature engineering process involves exploiting domain knowledge, applying intuition, and performing a time-consuming series of trial-and-error extractions. Manually overseeing this process significantly impacts the performance of model generation. We address this challenge with an automated feature engineering approach to extract the various features from blockchain transactions. Also, we engineered a set of new features based on statistical measures and graph representation. We demonstrate that the proposed approach can be applied to various blockchain transaction datasets, including Bitcoin and Ethereum. The engineered features were tested against eight classifiers, including random forest, XG-boost, Silas, and neural network-based classifiers to identify the suspicious behaviour of transactions</p>
Summary Outsourcing storage and computation to cloud servers have become a trend. Although searchable symmetric encryption (SSE) had handled the data privacy issue caused by honest‐but‐curious servers, a semi‐honest server may return incomplete or incorrect results when users search for their encrypted data. To against such servers, scholars have recently used blockchain/Ethereum‐based SSE schemes which utilize the public, that is, active nodes, to verify the search process. However, the search operation in existing schemes is very expansive in terms of fee and time. In this paper, we propose a new blockchain‐based searchable encryption framework with search optimized, that is, free of charge, quicker, and more private, at the cost of some extra storage. Besides, we design a general and efficient verification algorithm for our framework, which makes the search verifiable. In addition, we deploy an instance of our framework on an official Ethereum test network, and the experimental results and evaluations demonstrate the advantage of our framework.
<p>Non-fungible tokens (NFTs) have been attracting the interest of both technical and non-technical parties, including collectors and traders, among others. The number of transactions in NFTs surpassed $50 billion in 2022. Blockchain technology's advantages as a distributed, immutable, and transparent database make it ideal for verifying the ownership of digital goods created by their producers. On the other hand, high computation and transaction costs are known disadvantages of public blockchain networks like Ethereum V1, used in NFT marketplaces. To address these inefficiencies, other public blockchain systems have emerged as replacements for NFT marketplaces, each with its own unique properties. When planning such an NFT exchange, it is vital, but not trivial, to select the most appropriate public blockchain platform. In this work, we make two contributions to support this decision. In this paper, we present <em>IntelliChain</em>, a self-adaptive framework that can predict the best optimal transaction fees (also known as a gas fee) for blockchain to reduce the errors and also an ability to switch the public blockchain-based dynamic needs such as transaction fees and stability of the network.</p>
Smart contracts are programs that are executed on the blockchain and can hold, manage and transfer assets in the form of cryptocurrencies. The contract's execution is then performed on-chain and is subject to consensus, i.e. every node on the blockchain network has to run the function calls and keep track of their side-effects including updates to the balances and contract's storage. The notion of gas is introduced in most programmable blockchains, which prevents DoS attacks from malicious parties who might try to slow down the network by performing time-consuming and resource-heavy computations. While the gas idea has largely succeeded in its goal of avoiding DoS attacks, the resulting fees are extremely high. For example, in June-September 2022, on Ethereum alone, there has been an average total gas usage of 2,706.8 ETH ≈ 3,938,749 USD per day. We propose a protocol for alleviating these costs by moving most of the computation off-chain while preserving enough data on-chain to guarantee an implicit consensus about the contract state and ownership of funds in case of dishonest parties. We perform extensive experiments over 3,330 real-world Solidity contracts that were involved in 327,132 transactions in June-September 2022 on Ethereum and show that our approach reduces their gas usage by 40.09 percent, which amounts to a whopping 442,651 USD.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Charity organizations are susceptible to the same kinds of fraud that harm businesses because donors lack confidence in how their money is being used. the requirement to provide a unified platform for monitoring donations that will monitor all data related to donations transactions and donors Lack of trust on the part of donors in how donations are used is a result of skepticism over how donations are used. Building a single platform for tracking donations that would manage all information regarding gift transactions is essential since charities are vulnerable to fraud that affects corporations, such as executive misuse of funds and embezzlement. Keywords—Transparent system, Smart contract, Blockchain, Charity, Ethereum, Digital charity.
Rasoul Amirzadeh, Asef Nazari, Dhananjay Thiruvady, Mong Shan Ee
This study identifies the key factors influencing the price movements of major cryptocurrencies, Bitcoin, Binance Coin, Ethereum, Litecoin, Ripple, and Tether, using Bayesian networks (BNs). This study addresses two key challenges: modelling price movements in highly volatile cryptocurrency markets and enhancing predictive performance through discretisation-aware Bayesian Networks. It analyses both macro-financial indicators (gold, oil, MSCI, S and P 500, USDX) and social media signals (tweet volume) as potential price drivers. Moreover, since discretisation is a critical step in the effectiveness of BNs, we implement a structured procedure to build 54 BNs models by combining three discretisation methods (equal interval, equal quantile, and k-means) with several bin counts. These models are evaluated using four metrics, including balanced accuracy, F1 score, area under the ROC curve and a composite score. Results show that equal interval with two bins consistently yields the best predictive performance. We also provide deeper insights into each network's structure through inference, sensitivity, and influence strength analyses. These analyses reveal distinct price-driving patterns for each cryptocurrency, underscore the importance of coin-specific analysis, and demonstrate the value of BNs for interpretable causal modelling in volatile cryptocurrency markets.
Javier Ron, César Soto-Valero, Long Zhang, Benoit Baudry · 5 authors
As all software, blockchain nodes are exposed to faults in their underlying execution stack. Unstable execution environments can disrupt the availability of blockchain nodes interfaces, resulting in downtime for users. This paper introduces the concept of N-version Blockchain nodes. This new type of node relies on simultaneous execution of different implementations of the same blockchain protocol, in the line of Avizienis' N-version programming vision. We design and implement an N-version blockchain node prototype in the context of Ethereum, called N-ETH. We show that N-ETH is able to mitigate the effects of unstable execution environments and significantly enhance availability under environment faults. To simulate unstable execution environments, we perform fault injection at the system-call level. Our results show that existing Ethereum node implementations behave asymmetrically under identical instability scenarios. N-ETH leverages this asymmetric behavior available in the diverse implementations of Ethereum nodes to provide increased availability, even under our most aggressive fault-injection strategies. We are the first to validate the relevance of N-version design in the domain of blockchain infrastructure. From an industrial perspective, our results are of utmost importance for businesses operating blockchain nodes, including Google, ConsenSys, and many other major blockchain companies.
The blockchain 2.0 age, marked by smart contract and Ethereum, has arrived couple years ago. Its technologies have expanded the application scenarios of blockchain technology and driven the boom of decentralized Finance. However, smart contract vulnerabilities and security issues are also emerging one after another. Hackers have exploited these vulnerabilities to cause huge economic losses. In recent years, a large amount of research on the analysis and detection of smart contract vulnerabilities has emerged, but there has been no common detection tool and corresponding test dataset. In this paper, we build GSVD dataset (Generalized Smart Contract Vulnerability Dataset) consisting four offline datasets using smart contracts on two chains, Polygon and BSC: two small Solidity datasets consisting of 153 labeled smart contract source codes, which can be used to test the performance of vulnerability mining tools; two large Solidity datasets consisting of 52,202 un labeled real smart contract source codes that can be used to verify the correctness of various theories and tools under a large number of real data conditions. At the same time, this paper integrates the scripting framework accompanying the GSVD dataset, which can execute a variety of popular automated vulnerability detection tools on top of these datasets and generate analysis results of contracts and potential vulnerabilities. We tested the Minor dataset under GSVD using three tools (Slither, Manticore, Mythril) that are kept up to date and found that the combined use of all tools detected 61.1% of labeled vulnerabilities, of which Mythril has the highest detection rate of 42.6%. It is not difficult to conclude that there`re still ample room for advancement for current smart contract vulnerability mining tools because of their underlying methods. Besides, our dataset can contribute to the ultimate target greatly by providing mining tools plenty real contracts information.
Jing Huey Khor, Michail Sidorov, Seri Aathira Balqis Zulqarnain
Scalability prevents public blockchains from being widely adopted for Internet of Things (IoT) applications such as supply chain management. Several existing solutions focus on increasing the transaction count, but none of them address scalability challenges introduced by resource-constrained IoT device integration with these blockchains, especially for the purpose of supply chain ownership management. Thus, this paper solves the issue by proposing a scalable public blockchain-based protocol for the interoperable ownership transfer of tagged goods, suitable for use with resource-constrained IoT devices such as widely used Radio Frequency Identification (RFID) tags. The use of a public blockchain is crucial for the proposed solution as it is essential to enable transparent ownership data transfer, guarantee data integrity, and provide on-chain data required for the protocol. A decentralized web application developed using the Ethereum blockchain and an InterPlanetary File System is used to prove the validity of the proposed lightweight protocol. A detailed security analysis is conducted to verify that the proposed lightweight protocol is secure from key disclosure, replay, man-in-the-middle, de-synchronization, and tracking attacks. The proposed scalable protocol is proven to support secure data transfer among resource-constrained RFID tags while being cost-effective at the same time.
Closed-circuit television (CCTV) cameras and black boxes are indispensable for road safety and accident management. Visible highway surveillance cameras can promote safe driving habits while discouraging moving violations. According to CCTV laws, footage captured by roadside cameras must be securely stored, and authorized persons can access it. Footages collected by CCTV and Blackbox are usually saved to the camera’s microSD card, the cloud, or hard drives locally but there are concerns about security and data integrity. These issues may be addressed by blockchain technology. The cost of storing data on the blockchain, on the other hand, is prohibitively expensive. We can have decentralized and cost-effective storage with the interplanetary file system (IPFS) project. It is a file-sharing protocol that stores and distributes data in a distributed file system. We propose a decentralized IPFS and blockchain-based application for distributed file storage. It is possible to upload various types of files into our decentralized application (DApp), and hashes of the uploaded files are permanently saved on the Ethereum blockchain with the help of smart contracts. Because it cannot be removed, it is immutable. By clicking on the file description, we can also view the file. DApp also includes a keyword search feature to assist us in quickly locating sensitive information. We used Ethers.js’ smart contract event listener and contract.queryFilter to filter and read data from the blockchain. The smart contract events are then written to a text file for our DApp’s keyword search functionality. Our experiment demonstrates that our DApp is resilient to system failure while preserving the transparency and integrity of data due to the immutability of blockchain.
Asan Nainar, Vigneshwaran, S. Surya, Saran Kumar · 5 authors
This blockchain-based decentralized ecommerce project aims to create a platform that enables buyers and sellers to interact and transact directly without the need for intermediaries. The project utilizes blockchain technology to ensure security, transparency, and immutability of transactions, and also incorporates Firebase and Moralis Web3 to provide seamless integration with existing web platforms. Firebase is a cloud-based platform that offers various services, including authentication, real-time database, and hosting, which are crucial in providing a secure and efficient e-commerce experience. Moralis Web3, on the other hand, provides a backend-as-a-service for web3 applications, allowing developers to interact with the Ethereum blockchain easily. In summary, this blockchain-based decentralized e-commerce project offers an efficient, secure, and cost-effective platform for buyers and sellers to engage in transactions without intermediaries. The integration of Firebase and Moralis Web3 enhances the platform's usability, making it accessible to a wider audience.
A smart contract is a self-executing program on a blockchain to ensure an immutable and transparent agreement without the involvement of intermediaries. Despite its growing popularity for many blockchain platforms like Ethereum, no technical means is available even when a smart contract requires to be protected from being copied. One promising direction to claim a software ownership is software watermarking. However, applying existing software watermarking techniques is challenging because of the unique properties of a smart contract, such as a code size constraint, non-free execution cost, and no support for dynamic allocation under a virtual machine environment. This paper introduces a novel software watermarking scheme, dubbed Smartmark, aiming to protect the ownership of a smart contract against a pirate activity. Smartmark builds the control flow graph of a target contract runtime bytecode, and locates a collection of bytes that are randomly elected for representing a watermark. We implement a full-fledged prototype for Ethereum, applying Smartmark to 27,824 unique smart contract bytecodes. Our empirical results demonstrate that Smartmark can effectively embed a watermark into a smart contract and verify its presence, meeting the requirements of credibility and imperceptibility while incurring an acceptable performance degradation. Besides, our security analysis shows that Smartmark is resilient against viable watermarking corruption attacks; e.g., a large number of dummy opcodes are needed to disable a watermark effectively, resulting in producing an illegitimate smart contract clone that is not economical.
Blockchains are significantly easing trade finance, with billions of dollars worth of assets being transacted daily. However, analyzing these networks remains challenging due to the sheer volume and complexity of the data. We introduce a method named InnerCore that detects market manipulators within blockchain-based networks and offers a sentiment indicator for these networks. This is achieved through data depth-based core decomposition and centered motif discovery, ensuring scalability. InnerCore is a computationally efficient, unsupervised approach suitable for analyzing large temporal graphs. We demonstrate its effectiveness by analyzing and detecting three recent real-world incidents from our datasets: the catastrophic collapse of LunaTerra, the Proof-of-Stake switch of Ethereum, and the temporary peg loss of USDC - while also verifying our results against external ground truth. Our experiments show that InnerCore can match the qualified analysis accurately without human involvement, automating blockchain analysis in a scalable manner, while being more effective and efficient than baselines and state-of-the-art attributed change detection approach in dynamic graphs.
Zibin Zheng, Neng Zhang, Jianzhong Su, Zhijie Zhong · 6 authors
Smart contracts are programs deployed on a blockchain and are immutable once deployed. Reentrancy, one of the most important vulnerabilities in smart contracts, has caused millions of dollars in financial loss. Many reentrancy detection approaches have been proposed. It is necessary to investigate the performance of these approaches to provide useful guidelines for their application. In this work, we conduct a large-scale empirical study on the capability of five well-known or recent reentrancy detection tools such as Mythril and Sailfish. We collect 230,548 verified smart contracts from Etherscan and use detection tools to analyze 139,424 contracts after deduplication, which results in 21,212 contracts with reentrancy issues. Then, we manually examine the defective functions located by the tools in the contracts. From the examination results, we obtain 34 true positive contracts with reentrancy and 21,178 false positive contracts without reentrancy. We also analyze the causes of the true and false positives. Finally, we evaluate the tools based on the two kinds of contracts. The results show that more than 99.8% of the reentrant contracts detected by the tools are false positives with eight types of causes, and the tools can only detect the reentrancy issues caused by call.value(), 58.8% of which can be revealed by the Ethereum's official IDE, Remix. Furthermore, we collect real-world reentrancy attacks reported in the past two years and find that the tools fail to find any issues in the corresponding contracts. Based on the findings, existing works on reentrancy detection appear to have very limited capability, and researchers should turn the rudder to discover and detect new reentrancy patterns except those related to call.value().