Characterizing Code Clones in the Ethereum Smart Contract Ecosystem

He, Ningyu; Wu, Lei; Wang, Haoyu; Guo, Yao; Jiang, Xuxian

doi:10.1007/978-3-030-51280-4_35

Cited by 47 publications

(22 citation statements)

References 29 publications

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“…EOAs are controlled by private keys and have no associated bytecode, whereas CAs have associated code (known as smart contracts) and data storage. Both accounts can communicate with those identical to them and also with one another albeit in different ways [53]. The circulated currency between peers in the Ethereum network is known as Ether.…”

Section: ) Ethereummentioning

confidence: 99%

An Integrated Architecture for Maintaining Security in Cloud Computing Based on Blockchain

et al. 2021

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Due to its wide accessibility, cloud services are susceptible to attacks. Data manipulation is a serious threat to data integrity which can occur in cloud computing -a relatively new offering under the umbrella of cloud services. Data can be tampered with, and malicious actors could use this to their advantage. Cloud computing clients in various application domains want to be assured that their data is accurate and trustworthy. On another spectrum, blockchain is a tamper-proof digital ledger that can be used alongside cloud technology to provide a tamper-proof cloud computing environment. This paper proposes a scheme that combines cloud computing with blockchain that assures data integrity for all homomorphic encryption schemes. To overcome the cloud service provider's (CSP) ultimate authority over the data, the proposed scheme relies on the Byzantine Fault Tolerance consensus to build a distributed network of processing CSPs based on the client requirements. After certain computations performed by all CSPs, they produce a master hash value for their database. To ensure immutable data is produced, master hash values are preserved in Bitcoin or Ethereum blockchain networks. The master hash values can be obtained by tracking the block header address for verification purposes. A theoretical analysis of the overhead costs associated with creating master hash values for each of the cryptocurrencies is presented. We found that Ethereum leads to lower client financial costs and better online performance than Bitcoin. We also specify the data security requirements the proposed scheme provides, the ground-level implementation, and future work. The proposed verification scheme is based on public cryptocurrency as a back-end service and does not require additional setup actions by the client other than a wallet for the chosen cryptocurrency.

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Section: ) Ethereummentioning

confidence: 99%

An Integrated Architecture for Maintaining Security in Cloud Computing Based on Blockchain

et al. 2021

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“…Code Clones. To detect code clones, He et al [23] first de-duplicate contracts by 'removing function unrelated code (e.g., creation code and Swarm code), and tokenizing the code to keep opcodes only.' Then, they generate fingerprints of the de-duplicated contracts by a customized version of fuzzy hashing and compute pairwise similarity scores.…”

Section: Evm Bytecode Analysismentioning

confidence: 99%

Identification of token contracts on Ethereum: standard compliance and beyond

Angelo

Salzer

2021

Int J Data Sci Anal

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Next to cryptocurrencies, tokens are a widespread application area of blockchains. Tokens are digital assets implemented as small programs on a blockchain. Being programmable makes them versatile and an innovative means for various purposes. Tokens can be used as investment, as a local currency in a decentralized application, or as a tool for building an ecosystem or a community. A high-level categorization of tokens differentiates between payment, security, and utility tokens. In most jurisdictions, security tokens are regulated, and hence, the distinction is of relevance. In this work, we discuss the identification of tokens on Ethereum, the most widely used token platform. The programs on Ethereum are called smart contracts, which—for the sake of interoperability—may provide standardized interfaces. In our approach, we evaluate the publicly available transaction data by first reconstructing interfaces in the low-level code of the smart contracts. Then, we not only check the compliance of a smart contract with an established interface standard for tokens, but also aim at identifying tokens that are not fully compliant. Thus, we discuss various heuristics for token identification in combination with possible definitions of a token. More specifically, we propose indicators for tokens and evaluate them on a large set of token and non-token contracts. Finally, we present first steps toward an automated classification of tokens regarding their purpose.

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“…With the rapid development of blockchain's distribution architecture, the Ethereum smart contract provides an environment for malicious code clones by injecting a piece of contract code and propagating it to other blocks. He et al [52] focused on the ecosystem of the Ethereum smart contract to characterize vulnerable code clones using the fuzzy hashing technique to calculate the edit distance between two fingerprints. Their approach compares the similarity between generated fingerprints of user-created contract code and contract-created contract code during Ethereum virtual machine runtime.…”

Section: D: Ethereum Smart Contractmentioning

confidence: 99%

A Survey of Software Clone Detection From Security Perspective

Zhang

Sakurai

2021

IEEE Access

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In software engineering, if two code fragments are closely similar with minor modifications, or even identical as a result of copy-paste behavior, they are called software/code clones. Code clones can cause trouble in software maintenance and the debugging process because identifying all copied compromised code fragments in other locations is time-consuming. Researchers have been studying code clone detection issues for a long time, and the discussion mainly focuses on software engineering management and system maintenance. Another considerable issue is that code cloning provides an easy way for attackers to maliciously inject code. A thorough survey of code clone identification/detection from the security perspective is indispensable for providing a comprehensive review of previous related studies and proposing potential research directions. This paper satisfies the above requirements. We review and introduce previous security-related studies following three classifications and various comparison criteria. We then discuss three further research directions: (i) deep learning-based code clone vulnerability detection, (ii) vulnerable code clone detection for 5G-Internet of Things devices, and (iii) real-time detection methods for more efficiently detecting clone attacks. These methods are more advanced and adaptive to technological development and still have sufficient research space for future studies.

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Characterizing Code Clones in the Ethereum Smart Contract Ecosystem

Cited by 47 publications

References 29 publications

An Integrated Architecture for Maintaining Security in Cloud Computing Based on Blockchain

An Integrated Architecture for Maintaining Security in Cloud Computing Based on Blockchain

Identification of token contracts on Ethereum: standard compliance and beyond

A Survey of Software Clone Detection From Security Perspective

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