# Modified Genetic Algorithm with Deep Learning for Fraud Transactions of Ethereum Smart Contract
## 1 Introduction  
Ethereum is a decentralized blockchain platform and famous cryptocurrency alternate platform, in addition to the most well-known platform for peer-to-peer programming. The security of blockchain technology and supervision has been recently receiving much attention. This open-source blockchain technology may be used to create smart contracts. Its development resolves the issue of Bitcoin's restricted scalability. Because of the versatility of the Solidity language, developers may create general-purpose smart contracts. Among the various smart contracts, some may be fraudulent, taking ether from network participants. Ethereum has risen rapidly because of its simplicity and versatility. Ethereum is currently the second most valuable cryptocurrency, only after Bitcoin. Bitcoin and Ethereum have gained in popularity as a result of their creation by [PERSON] et al. [1], [PERSON] and [PERSON] [2], and [PERSON] and [PERSON] [3]. The major purpose is to empower individuals by allowing employers to manage their own data and transactions. One such cryptocurrency is Ethereum, which was established by [PERSON]. In brief, Ethereum is a cryptocurrency allocation system that allows a user to send fractional cryptocurrency to anybody at a low cost; because Ethereum is built on a blockchain network, everyone may use the digital transactions, with extremely minimal transaction fees, in a secure manner. The vast user base of Ethereum encourages developers to release their programs on the network, further solidifying Ethereum as the primary platform for decentralized programs such as DeFi andNFTs. A much more scalable infrastructure will soon be made available by the backwards-compatible Ethereum 2.0 protocol, allowing developers to create decentralized apps with higher transaction throughput. A smart contract is a part of an existing application that is stored at a particular contract location on the blockchain. Apps can invoke the functionalities of smart contracts, alter their states, and start transactions [4; 5]. The Ethereum Virtual Machine (EVM) compiles programming languages such as Solidity and Vyper into bytecode, which is then used to implement smart contracts on the blockchain technology. The growth of artificial intelligence (AI) and various mining techniques has increased the demand to exchange the most diversified data; however, fraudulent activities have also appeared in online services. Unfortunately, the development of these data pertains to numerous distinct security sectors, so sharing them is difficult, especially when they contain information that requires privacy and security. The integration of automation in blockchain has resulted in the fast acceptance of the technology in several industries, such as online finance, the Internet of Things (IoT), supply chain management, healthcare, insurance, and so on [6; 7]. Blockchain is a global and immutable ledger that makes it easier to record transactions between both receiving and sending parties and monitor assets in a corporate network. Meanwhile, Ethereum is a P2P network for securely implementing and verifying application code, referred to as smart contract accounts. Smart contracts enable parties to transact with one another even without a trusted centralized government. There is a concern that criminal transactions may be concealed. However, owing to the nature of the blockchain, all transaction data are public, and anybody may obtain transaction information. Nevertheless, as wallets and transactions for cryptocurrencies grow in quantity and become more common, detection becomes increasingly difficult. The fact that the blockchain is decentralized indicates that no one entity has control over it. If a scam occurs, it would be difficult to identify the perpetrators. These concerns, along with the users' anonymity, may lead to fraudulent activity. The detection of suspicious transactions in such vast financial transaction networks has been the subject of several research works.