Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Ethereum Fraud Detection Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/vagifa/ethereum-frauddetection-dataset on 13 November 2021.
--- Dataset description provided by original source is as follows ---
This dataset contains rows of known fraud and valid transactions made over Ethereum, a type of cryptocurrency. This dataset is imbalanced, so keep that in mind when modelling
Here is a description of the rows of the dataset:
Total_Transactions(Including_Tnx_to_Create_Contract): Total number of transactions
Total_Ether_Sent:Total Ether sent for account address
Total_Ether_Received: Total Ether received for account address
Total_Ether_Sent_Contracts: Total Ether sent to Contract addresses
Total_Ether_Balance: Total Ether Balance following enacted transactions
Total_ERC20_Tnxs: Total number of ERC20 token transfer transactions
ERC20_Total_Ether_Received: Total ERC20 token received transactions in Ether
ERC20_Total_Ether_Sent: Total ERC20token sent transactions in Ether
ERC20_Total_Ether_Sent_Contract: Total ERC20 token transfer to other contracts in Ether
ERC20_Uniq_Sent_Addr: Number of ERC20 token transactions sent to Unique account addresses
ERC20_Uniq_Rec_Addr: Number of ERC20 token transactions received from Unique addresses
ERC20_Uniq_Rec_Contract_Addr: Number of ERC20token transactions received from Unique contract addresses
ERC20_Avg_Time_Between_Sent_Tnx: Average time between ERC20 token sent transactions in minutes
ERC20_Avg_Time_Between_Rec_Tnx: Average time between ERC20 token received transactions in minutes
ERC20_Avg_Time_Between_Contract_Tnx: Average time ERC20 token between sent token transactions
ERC20_Min_Val_Rec: Minimum value in Ether received from ERC20 token transactions for account
ERC20_Max_Val_Rec: Maximum value in Ether received from ERC20 token transactions for account
ERC20_Avg_Val_Rec: Average value in Ether received from ERC20 token transactions for account
ERC20_Min_Val_Sent: Minimum value in Ether sent from ERC20 token transactions for account
ERC20_Max_Val_Sent: Maximum value in Ether sent from ERC20 token transactions for account
ERC20_Avg_Val_Sent: Average value in Ether sent from ERC20 token transactions for account
ERC20_Uniq_Sent_Token_Name: Number of Unique ERC20 tokens transferred
ERC20_Uniq_Rec_Token_Name: Number of Unique ERC20 tokens received
ERC20_Most_Sent_Token_Type: Most sent token for account via ERC20 transaction
ERC20_Most_Rec_Token_Type: Most received token for account via ERC20 transactions
--- Original source retains full ownership of the source dataset ---
http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
A dataset containing fraud and valid ethereum transactions
http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
This dataset contains rows of known fraud and valid transactions made over Ethereum, a type of cryptocurrency. This dataset is imbalanced, so keep that in mind when modelling
Here is a description of the rows of the dataset:
Total_Transactions(Including_Tnx_to_Create_Contract): Total number of transactions
Total_Ether_Sent:Total Ether sent for account address
Total_Ether_Received: Total Ether received for account address
Total_Ether_Sent_Contracts: Total Ether sent to Contract addresses
Total_Ether_Balance: Total Ether Balance following enacted transactions
Total_ERC20_Tnxs: Total number of ERC20 token transfer transactions
ERC20_Total_Ether_Received: Total ERC20 token received transactions in Ether
ERC20_Total_Ether_Sent: Total ERC20token sent transactions in Ether
ERC20_Total_Ether_Sent_Contract: Total ERC20 token transfer to other contracts in Ether
ERC20_Uniq_Sent_Addr: Number of ERC20 token transactions sent to Unique account addresses
ERC20_Uniq_Rec_Addr: Number of ERC20 token transactions received from Unique addresses
ERC20_Uniq_Rec_Contract_Addr: Number of ERC20token transactions received from Unique contract addresses
ERC20_Avg_Time_Between_Sent_Tnx: Average time between ERC20 token sent transactions in minutes
ERC20_Avg_Time_Between_Rec_Tnx: Average time between ERC20 token received transactions in minutes
ERC20_Avg_Time_Between_Contract_Tnx: Average time ERC20 token between sent token transactions
ERC20_Min_Val_Rec: Minimum value in Ether received from ERC20 token transactions for account
ERC20_Max_Val_Rec: Maximum value in Ether received from ERC20 token transactions for account
ERC20_Avg_Val_Rec: Average value in Ether received from ERC20 token transactions for account
ERC20_Min_Val_Sent: Minimum value in Ether sent from ERC20 token transactions for account
ERC20_Max_Val_Sent: Maximum value in Ether sent from ERC20 token transactions for account
ERC20_Avg_Val_Sent: Average value in Ether sent from ERC20 token transactions for account
ERC20_Uniq_Sent_Token_Name: Number of Unique ERC20 tokens transferred
ERC20_Uniq_Rec_Token_Name: Number of Unique ERC20 tokens received
ERC20_Most_Sent_Token_Type: Most sent token for account via ERC20 transaction
ERC20_Most_Rec_Token_Type: Most received token for account via ERC20 transactions
https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.null/customlicense?persistentId=doi:10.34894/GKAQYNhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.null/customlicense?persistentId=doi:10.34894/GKAQYN
The recent technological advent of cryptocurrencies and their respective benefits have been shrouded with a number of illegal activities operating over the network such as money laundering, bribery, phishing, fraud, among others. In this work we focus on the Ethereum network, which has seen over 400 million transactions since its inception. Using 2179 accounts flagged by the Ethereum community for their illegal activity coupled with 2502 normal accounts, we seek to detect illicit accounts based on their transaction history using the XGBoost classifier. Using 10 fold cross-validation, XGBoost achieved an average accuracy of 0.963 ( ± 0.006) with an average AUC of 0.994 ( ± 0.0007). The top three features with the largest impact on the final model output were established to be ‘Time diff between first and last (Mins)’, ‘Total Ether balance’ and ‘Min value received’. Based on the results we conclude that the proposed approach is highly effective in detecting illicit accounts over the Ethereum network. Our contribution is multi-faceted; firstly, we propose an effective method to detect illicit accounts over the Ethereum network; secondly, we provide insights about the most important features; and thirdly, we publish the compiled data set as a benchmark for future related works.
Cryptocurrency, as blockchain’s most famous implementation, suffers a huge economic loss due to phishing scams. In our work, accounts and transactions in Ethereum are treated as nodes and edges, thus detection of phishing accounts can be modeled as a node classification problem.
In this work, we collected phishing nodes from Ethereum that reported in Etherscan labeled cloud. Starting from phishing nodes we crawl a huge Ethereum transaction network via second-order BFS. Dataset contains 2,973,489 nodes, 13,551,303 edges and 1,165 labeled nodes.
MulDiGraph.pkl:This dataset is stored in pickle format, and it is the networkx object. Each node is an address with an attribute called isp indicating whether it is a phishing node. Each edge has two attributes, including amount and timestamp, which represent the balance of the transaction and the timestamp of the transaction, respectively. In this data set, the total number of nodes is 2,973,489, the number of transactions is 13,551,303, and the average degree is 4.5574.
For more details about blockchain dataset, please click here.
The recent technological advent of cryptocurrencies and their respective benefits have been shrouded with a number of illegal activities operating over the network such as money laundering, bribery, phishing, fraud, among others. In this work we focus on the Ethereum network, which has seen over 400 million transactions since its inception. Using 2179 accounts flagged by the Ethereum community for their illegal activity coupled with 2502 normal accounts, we seek to detect illicit accounts based on their transaction history using the XGBoost classifier. Using 10 fold cross-validation, XGBoost achieved an average accuracy of 0.963 ( ± 0.006) with an average AUC of 0.994 ( ± 0.0007). The top three features with the largest impact on the final model output were established to be ‘Time diff between first and last (Mins)’, ‘Total Ether balance’ and ‘Min value received’. Based on the results we conclude that the proposed approach is highly effective in detecting illicit accounts over the Ethereum network. Our contribution is multi-faceted; firstly, we propose an effective method to detect illicit accounts over the Ethereum network; secondly, we provide insights about the most important features; and thirdly, we publish the compiled data set as a benchmark for future related works.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This dataset was created by Guille Escobero
Released under CC0: Public Domain
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This dataset was created by vasavi chithanuru
Released under MIT
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The comparison between (smart contract)-based delegate contract signing and traditional delegate contract signing.
https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy
The Global Smart Contracts Market Size is projected to grow from USD XX billion in 2021 to USD XX billion by 2028, at an estimated CAGR of 34.8% during the forecast period (2021-2028). The market is driven by factors such as the increasing need for automation, integration with various technologies and systems, and high scalability potential among others.
Smart contracts are self-executing digital agreements that can carry out the direct transaction of assets between untrusted agents. Smart Contracts allow for formal verification, which helps to ensure there is no misbehavior and protects you from fraud. Blockchain technology enables a secure way to create these contracts without any third-party interference directly between peers.
On the basis of Type, the market is segmented into Bitcoin, Sidechains, NXT, and Ethereum.
Bitcoin is a decentralized peer-to-peer Digital Currency that enables instant payments to anyone, anywhere in the world. Bitcoin uses blockchain technology to record its transactions. Blockchain is a public ledger of all Bitcoin transactions.
Sidechains are decentralized, peer-to-peer networks that provide connectivity between different blockchains.
NXT is an open-source Cryptocurrency and payment network that uses proof of stake to reach a consensus for transactions. NXT was conceived by BCNext, whose goal was to create a platform on which decentralized applications could be built in the future.
Ethereum is a decentralized platform that runs "smart contracts" or self-executing transactions, which do not rely on any central server for processing. These smart contracts run on the Ethereum Virtual Machine (EVM) and can be written in Solidity language, Serpent language, and LLL programming languages.
On the basis of Application, the market is segmented into Banking, Government, Management, Supply Chain, Automobile, Real Estate, Insurance, and Healthcare.
The use of smart contracts in banking can dramatically reduce the time and cost associated with financial transactions. The implementation of Smart Contracts by banks allows for improved processes such as reconciliation, settlement, identity management, regulatory compliance, and trading surveillance.
Smart Contracts can be used in Government to make the process more transparent and efficient.
In management, smart contracts are used to ensure the security and integrity of critical business processes. It is a digital alternative to traditional contract law. With this technology, contractual agreements can be executed automatically without human intervention while ensuring transparency for all concerned parties.
The use of Smart Contracts in the Supply Chain is to track and monitor requirements, inventory levels, production schedules, shipments, and more. This will also help with fulfillment management as a whole for both suppliers and customers involved in the process.
Smart contracts in the automotive industry are generally utilized to facilitate payments between two parties. Smart contracts also provide a safe and secure method for making payments without any additional transaction fees or intermediary involvement by banks, government authorities, etc., which can be both time-consuming and costly.
The use of Smart Contracts in Real Estate is for creating a record of the terms and conditions that are to be followed while executing real estate transactions. They ensure security, accuracy, transparency, and speed with their recording procedure which includes Digital Signatures from all concerned parties at every stage.
The use of smart contracts in Insurance can provide a higher level of automation by facilitating policy underwriting, claims processing, and payments. This will reduce delays between all parties involved.
In healthcare, smart contacts for payment and adherence to treatment protocols can potentially reduce costs. It is a secure method of transmitting patient data allowing doctors immediate access to their records while minimizing risks associated with storing information in multiple locations.
On the basis of Region, the market is segmented into North Amer
This dataset was created by Pablo Garcia Carreira
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Dataset contains 8.5M+ Ethereum block data. Ethereum is an open-source, blockchain-based, decentralized software platform used for its own cryptocurrency, ether. It enables Smart-Contracts and Distributed Applications (ĐApps) to be built and run without any downtime, fraud, control, or interference from a third party. To learn more about ethereum, visit here.
Dataset contains columns such as - Block Height - Block Hash - Block created timestamp - Miner details - Block size - Block Reward - Total Transactions in that block - Gas Limit and many more.
To get the scraping script of this data, go to my github link provided below
https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy
The global Mortgage Lender Market size was USD 1,024.6 Billion in 2023 and is projected to reach USD 3,077.9 Billion by 2032, expanding at a CAGR of 13% during 2024–2032. The market is fueled by the increasing demand for housing due to population growth and the advancement of digital mortgage platforms enhancing loan processing efficiency.
Rising demand for efficiency and speed in mortgage processing propels the adoption of digital and automated solutions in the market. Financial technology firms have revolutionized loan processing with AI-driven algorithms, reducing approval times from weeks to mere days.
Blockchain technology enhances transparency and security, mitigating fraud risks. Moreover, the integration of big data analytics enables lenders to offer personalized mortgage solutions, improving customer satisfaction and loyalty.
In February 2023, Roofstock, a premier digital platform for single-family rental properties, completed the sale of an Alabama rental through its web3 arm, Roofstock onChain, utilizing non-fungible token (NFT) technology on the Ethereum Blockchain. This transaction showcases the application of Teller Protocol's flexible DeFi lending solutions in real estate, facilitated by USDC.Homes, a marketplace powered by Teller Protocol for streamlined real estate financing.
Increasing awareness of environmental issues drives the market toward sustainable and green financing. Lenders are introducing eco-friendly mortgage products that offer lower interest rates for energy-efficient homes, encouraging sustainable development.
Government incentives for green buildings further fuel this trend, making eco-conscious mortgages attractive to borrowers. This shift addresses climate change and opens new market segments for lenders focusing on sustainability.
<span style="font-size:11pt&qu
The value of crypto lost to security threats grew over nine times between 2020 and 2021, with one incident in August 2021 accounting for 610 million U.S. dollars stolen. During this particular incident - claimed to be one of the biggest cryptocurrency heists of all time - an individual person targeted the Ethereum-based DeFi application Poly Network after exploited a flaw in the Network's code. After Poly Network pleaded with the hacker, the anonymous hacker handed back about half of the money - 342 million U.S. dollars - claiming he did the hack "for fun".
In 2020, the distribution of the global blockchain market revenue was heavily distributed towards the banking industry, which has a market share of almost 30 percent. While process manufacturing accounted for 11.4 percent of worldwide blockchain spending. Overall, the global spending on blockchain solutions is continued to grow in the upcoming years.
Blockchain technology
Simply put, blockchain is a distributed ledger technology, which creates assurance between trading partners, especially in trades that occur with cryptocurrency. For example, in the case of Bitcoin and Ethereum, blockchain is the technology that allows for the transfer of these cryptocurrencies, providing confidence in financial transactions. This additional confidence through the usage of blockchain comes from the reduced fraud, increased financial inclusion, and decreased costs. This leads to the simplification of cross-border payments and settlements, which has the potential to change the global banking industry as we know it.
Blockchain and Bitcoin Blockchain and Bitcoin have a symbiotic relationship as blockchain technology was created to be a database structured into “blocks” of data that is linked, or in other words, “chained”, to other sets of data. The blockchain technology stores the Bitcoin transactions in a continuous linked structure, that continues to increase with time and each transaction. Hence, with the increased popularity of Bitcoin comes the increased importance of the growing Bitcoin blockchain, which is visible in the increased number of blockchain wallet users worldwide in the past few years alone.
https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice
Exploring the Lucrative Blockchain Market: Trends, Opportunities and Growth 2024-2028
The global Blockchain Market in Supply Chain Industry is projected to reach USD 8.55 billion in 2027, with a CAGR of 53.59% between 2023 and 2028. The growth rate of the market depends on several factors, including the growing number of cargo thefts, increasing complexities due to time-bound deliveries and customization of the supply chain, and the booming e-commerce industry.
Market Overview and Trends
Analysis Period
2018-2028
Market Size (2018) Historic Year
USD 0.21 billion
Market Size (2028) - Forecasted Year
USD 8.55 billion
Historic Opportunity (2018-2022)
USD 0.48 billion
Historic CAGR
34.33 %
Forecasted Opportunity (2024-2028)
USD 7.55 billion
Market Opportunity Transformation Growth
3.00 %
Market Opportunity Capitalization
USD 8.02 billion
The blockchain market is a rapidly growing sector in the technology industry. Blockchain technology offers secure and transparent transactions without the need for intermediaries. Major industries such as finance, supply chain management, and healthcare are adopting blockchain solutions.
Market Overview
For More Highlights About this Report, Download Free Sample in a Minute
Future Outlook of the Blockchain Market
Cryptocurrencies like Bitcoin and Ethereum are built on blockchain technology and have fueled the growth of the blockchain market. By 2023, it is estimated that the blockchain-based identity management market will exceed USD1 billion, providing secure and self-sovereign digital identities for individuals. Over 60% of major banks are expected to use blockchain technology for cross-border payments by 2024. The adoption of blockchain technology in supply chain management is anticipated to reduce costs by up to 20%.
Definition and Evolution of Blockchain Technology
The market for blockchain in the supply chain industry refers to the use of blockchain technology to enhance and revolutionize various aspects of supply chain management. Blockchain is a decentralized and transparent digital ledger that records transactions and interactions in a secure and immutable way. In the supply chain industry, blockchain technology can be utilized to streamline and optimize processes such as tracking and tracing products, ensuring transparency and authenticity of products, improving supply chain visibility, reducing fraud, and enhancing trust among stakeholders.
Market Growth and Forecasting
The increasing complexities due to time-bound deliveries and customization of the supply chain are notably driving the market growth. Selecting or formulating the right supply chain model is vital and critical. This is because customers prefer shorter lead times, while logistics and supply chain companies seek to keep the operational cost as low as possible. Various products such as chemicals, clinical, pharmaceuticals, and perishable food and beverages require special care and attention, specific packaging, and a customized supply chain for sustaining the physical and chemical properties of the shipped product.
In addition, the supply chain complexities vary with rural infrastructure based on topography, technology advances, and region/country-specific regulations and policies. For instance, the supply chain of pharmaceutical logistics in rural areas is different compared to that in urban areas. Rural areas lack logistical and technological infrastructure. Therefore, companies and end-user industries are availing blockchain technology to streamline their business operations and maintain high efficiency and agility in the supply chain. Hence, these factors are expected to drive market growth during the forecast period.
Industries Benefiting from Blockchain Adoption
The blockchain technology market has witnessed significant growth, driven by increased investments and the adoption of blockchain by various institutions. The transformative potential of blockchain extends to diverse industries, providing tangible benefits such as enhanced security, transparency, and efficiency. Notably, blockchain fosters innovation in financial transactions, allowing seamless transfer of money. Small and medium-sized enterprises (SMEs) leverage blockchain's decentralized database for improved operations. The adoption of blockchain extends to various use cases, including the creation of a secure and decentralized network.
Market Trends and Analysis
The emergence of blockchain-as-a-service is the key trend in the market. Blockchain-as-a-service is defined as a service in which companies set up the blockchain-connected nodes on the enterprise's behalf and also manage it at the back end. The growing evolution of the blockchain-as-a-service is encouraging companies through its subsidiary Amazon Web Services (AWS), and SAP to invest in the tec
https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy
The Global Blockchain Supplychain Market size is expected to grow from USD 6.21 Billion in 2021 to USD XX Billion by 2028, at a CAGR of 28.7% during the forecast period. The growth of this market can be attributed to the increasing demand for distributed ledger technology across industries, rising fraudulent activities across supply chains, and the growing need for transparency and immutability in supply chains.
The blockchain supply chain is the application of blockchain technology in the field of supply chain management. The blockchain supply chain provides a secure and transparent way to track and manage goods throughout the entire supply-chain process. It can be used to record any type of information related to the supply-chain process, such as shipment tracking, product history, quality control, and more. The blockchain-based supply chain offers transparency, security, and efficiency to businesses.
On the basis of Type, the market is segmented into Public Blockchain, Private Blockchain, and Consortium Blockchain. The Public Blockchain segment is expected to hold the largest market share during the forecast period.
A public blockchain is a distributed ledger technology that enables anyone to read or write to the ledger. Transactions on a public blockchain are transparent and can be verified by anyone. Public blockchains are typically permissionless, meaning anyone can participate in the network without having to ask for permission. Bitcoin and Ethereum are two examples of public blockchains. Public blockchains have several advantages over private blockchains. First, they are more secure because they have more nodes (computers) verifying transactions. Second, they are more decentralized, meaning there is no one party controlling the network. This makes them less vulnerable to censorship or attacks.
A private blockchain is a permissioned network where only authorized nodes can participate in the network. These nodes are typically known to each other and trust is established among them. The transactions on a private blockchain are verified by a set of trusted nodes instead of using a Proof-of-Work (PoW) algorithm. Private blockchains are ideal for businesses that want to keep their data private and secure.
A consortium blockchain is a blockchain where the nodes or participants are restricted to a certain group. Consortium blockchains are somewhere in between, with some restrictions on who can join, but not as tight as private blockchains. The consortium members could be companies, organizations, or individuals that have come together for a specific task or business goal.
On the basis of Application, the market is segmented into Retail, Oil & Gas, Healthcare, IT & Telecom, and Others. The Retail segment is expected to hold the largest market share during the forecast period.
Blockchain technology is being used in the retail sector for a number of reasons. These include tracking the movement of products, preventing counterfeiting, and improving customer experiences. In particular, retailers are interested in the use of blockchain to create transparent and secure supply chains. This allows customers to trust that they are getting what they paid for and that the products they purchase have not been tampered with. Additionally, by reducing waste and improving inventory management, blockchain can help retailers save money. Some companies are already implementing these applications and seeing positive results.
Oil and gas are one of the most important industrial sectors in the world. Blockchain technology has a lot to offer in this sector as well. Some of the possible uses of blockchain supply chain in oil and gas are Tracking and tracing of oil products throughout the supply chain; Preventing fraud by tracking product origins; Improved security due to immutable ledger; Reduced administrative costs; Real-time monitoring of supplier performance; Enhanced communication between producers and consumers.
The healthcare sector is one of the most important sectors that is looking to adopt blockchain technology. The reason for this is that the healthcare sector is rife with inefficiencies and problems that can be solved with blockchain technology. Some of the areas where blockchain supply chain can be used in the healthcare sector include Tracking Drugs: One of the biggest problems in the pharmaceutical industry is counterfeit drugs. The blockchain supply chain can help track drugs from manufact
The Ethereum blockchain gives a revolutionary way of decentralized applications and provides its own cryptocurrency. Ethereum is a decentralized platform that runs smart contracts: applications that run exactly as programmed without any possibility of downtime, censorship, fraud or third party interference. These apps run on a custom built blockchain, an enormously powerful shared global infrastructure that can move value around and represent the ownership of property. This enables developers to create markets, store registries of debts or promises, move funds in accordance with instructions given long in the past (like a will or a futures contract) and many other things that have not been invented yet, all without a middle man or counterparty risk.
What you may see in the CSVs are just numbers, but there is more to this. Numbers make machine learning easy. I've labeled each column, the first in all of them is the day; it may look weird but it makes sense if you look closely.
TIMESTAMP FORMAT
import datetime as dt
# The (would-be) timestamp value is below
timestamp = 1339521878.04
# Technechly you would iterate through and change them all if you were graphing
timeValue = dt.datetime.fromtimestamp(timestamp)
#Year, month, day, hour, minute, second
print(timeValue.strftime('%Y-%m-%d %H:%M:%S'))
MR. Vitalik Buterin. co-founder of Ethereum and as a co-founder of Bitcoin Magazine.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
If you reach this DATASET, please UPVOTE this dataset to show your appreciation
Ethereum (ETH) is a smart contract platform that enables developers to build decentralized applications (DAPs) conceptualized in Vitalik Buterin 2013. ETH is the local currency of the Ethereum platform and also serves as a transaction fee for miners in the Ethereum network.
Ethereum is the pioneer of blockchain-based smart contracts. Smart contract becomes a self-operating computer program when running on the blockchain, which automatically executes when certain conditions are met. On the blockchain, smart contracts allow the code to be programmed without the possibility of useless time, censorship, fraud or third party interference. It facilitates the conversion of money, content, property, shares or anything valuable. Ethereum Network went live on July 30, 2015 with 72 million Ethereum Premium.
https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F2533028%2F776eb982d1ce67447534edb8325b5540%2FOpera%20Snapshot_2020-04-16_121111_coinmarketcap.com.png?generation=1587019388673274&alt=media" alt="">
I encourage you to use this Dataset to start your own projects. If you do, please cite the Dataset: author = {Prasoon Kottarathil}, title = {Ethereum Historical Dataset}, year = {2020}, publisher = {kaggle}, journal = {Kaggle Dataset}, how published = {\url{https://www.kaggle.com/prasoonkottarathil/ethereum-historical-dataset}}
Not seeing a result you expected?
Learn how you can add new datasets to our index.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Ethereum Fraud Detection Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/vagifa/ethereum-frauddetection-dataset on 13 November 2021.
--- Dataset description provided by original source is as follows ---
This dataset contains rows of known fraud and valid transactions made over Ethereum, a type of cryptocurrency. This dataset is imbalanced, so keep that in mind when modelling
Here is a description of the rows of the dataset:
Total_Transactions(Including_Tnx_to_Create_Contract): Total number of transactions
Total_Ether_Sent:Total Ether sent for account address
Total_Ether_Received: Total Ether received for account address
Total_Ether_Sent_Contracts: Total Ether sent to Contract addresses
Total_Ether_Balance: Total Ether Balance following enacted transactions
Total_ERC20_Tnxs: Total number of ERC20 token transfer transactions
ERC20_Total_Ether_Received: Total ERC20 token received transactions in Ether
ERC20_Total_Ether_Sent: Total ERC20token sent transactions in Ether
ERC20_Total_Ether_Sent_Contract: Total ERC20 token transfer to other contracts in Ether
ERC20_Uniq_Sent_Addr: Number of ERC20 token transactions sent to Unique account addresses
ERC20_Uniq_Rec_Addr: Number of ERC20 token transactions received from Unique addresses
ERC20_Uniq_Rec_Contract_Addr: Number of ERC20token transactions received from Unique contract addresses
ERC20_Avg_Time_Between_Sent_Tnx: Average time between ERC20 token sent transactions in minutes
ERC20_Avg_Time_Between_Rec_Tnx: Average time between ERC20 token received transactions in minutes
ERC20_Avg_Time_Between_Contract_Tnx: Average time ERC20 token between sent token transactions
ERC20_Min_Val_Rec: Minimum value in Ether received from ERC20 token transactions for account
ERC20_Max_Val_Rec: Maximum value in Ether received from ERC20 token transactions for account
ERC20_Avg_Val_Rec: Average value in Ether received from ERC20 token transactions for account
ERC20_Min_Val_Sent: Minimum value in Ether sent from ERC20 token transactions for account
ERC20_Max_Val_Sent: Maximum value in Ether sent from ERC20 token transactions for account
ERC20_Avg_Val_Sent: Average value in Ether sent from ERC20 token transactions for account
ERC20_Uniq_Sent_Token_Name: Number of Unique ERC20 tokens transferred
ERC20_Uniq_Rec_Token_Name: Number of Unique ERC20 tokens received
ERC20_Most_Sent_Token_Type: Most sent token for account via ERC20 transaction
ERC20_Most_Rec_Token_Type: Most received token for account via ERC20 transactions
--- Original source retains full ownership of the source dataset ---