SoliAudit: Smart Contract Vulnerability Assessment Based on Machine Learning and Fuzz Testing

Liao, Jianwei; Tsai, Tsung-Ta; He, Chia-Kang; Tien, Chin‐Wei

doi:10.1109/iotsms48152.2019.8939256

Cited by 89 publications

(66 citation statements)

References 4 publications

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“…e current smart contract vulnerability detection methods mainly focus on symbolic execution and dynamic execution methods with low accuracy. Liao et al proposed a smart contract vulnerability detection method [47], namely, SoliAudit. is method used both static and dynamic testing technologies and enhanced smart contract vulnerability detection capabilities through machine learning and dynamic fuzzers.…”

Section: Security Applicationsmentioning

confidence: 99%

Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work

Zhang¹,

Song

Liu

et al. 2021

Security and Communication Networks

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Blockchain constructs a distributed point-to-point system, which is a secure and verifiable mechanism for decentralized transaction validation and is widely used in financial economy, Internet of Things, large data, cloud computing, and edge computing. On the other hand, artificial intelligence technology is gradually promoting the intelligent development of various industries. As two promising technologies today, there is a natural advantage in the convergence between blockchain and artificial intelligence technologies. Blockchain makes artificial intelligence more autonomous and credible, and artificial intelligence can prompt blockchain toward intelligence. In this paper, we analyze the combination of blockchain and artificial intelligence from a more comprehensive and three-dimensional point of view. We first introduce the background of artificial intelligence and the concept, characteristics, and key technologies of blockchain and subsequently analyze the feasibility of combining blockchain with artificial intelligence. Next, we summarize the research work on the convergence of blockchain and artificial intelligence in home and overseas within this category. After that, we list some related application scenarios about the convergence of both technologies and also point out existing problems and challenges. Finally, we discuss the future work.

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Section: Security Applicationsmentioning

confidence: 99%

Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work

Zhang¹,

Song

Liu

et al. 2021

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…Many studies are continuing to ensure the security of smart contracts. [44][45][46][47][48][49] Smart contract, which can help the developer to deploy the decentralized and secure Blockchain application, is one of the most promising technologies for the modern Internet of Things (IoT) ecosystem today. [50][51][52] However, Ethereum smart contract does not have the ability to communicate with the external IoT environment.…”

Section: Smart Contractsmentioning

confidence: 99%

A survey: Making “Smart Contracts” really smart

Timuçin

Biroğul

2021

Trans Emerging Tel Tech

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Blockchain technology is a distributed data recording system developed to monitor and secure all encrypted transactions with the shortest identification. Blockchain technology made a name for itself in 2008. However, the real development of this technology has been realized with use of smart contracts in Blockchain technology. In the cryptocurrency world, a smart contract can be defined as an application or program running on the Blockchain. They operate as digital deals that have to comply with certain rules. These rules are predetermined by computer codes and then copied and implemented by the servers in the entire network. The use of the word "smart" as a term in smart contracts comes from the fact that it is not made manually and is realized digitally. In this study, it is aimed to contribute to future studies in the transformation of smart contracts into real "smart" contract structures by applying artificial intelligence algorithms.

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“…Specifically, AI algorithms can strengthen the vulnerability detection capabilities of smart contract, enabling BC to analyze and detect defects without requiring predefined or expert knowledge, which will be successfully applied to the edge network [158]. ML can be combined with fuzz testing for smart contract vulnerability assessment, and this incorporation can rapidly adapt to new unknown weaknesses [159]. Moreover, learning vector representation (structural code embeddings) for smart contracts with the DL-based approach is useful in response to bugs and exploits created by attackers [160].…”

Section: Improve Performancementioning

confidence: 99%

Synergy of Edge Intelligence and Blockchain: A Comprehensive Survey

Wang¹,

Ren²,

Qiu³

et al. 2021

Preprint

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Edge intelligence (EI), as an emerging technology, has been attracting significant attention. It pushes the frontier of artificial intelligence (AI) from the cloud to the network edge, aiming to embrace and support the next-generation communications while unleashing AI services. However, it faces challenges in its decentralized management and security, which limit its capabilities to support services with numerous requirements. On the other side, blockchain (BC), as a promising decentralized technology, is beneficial to tackle the above issues. However, there exist some technical challenges for BC, such as transaction capacity, scalability, and fault tolerance. Motivated by significant current interest around EI and BC, this survey examines whether the synergy of EI and BC can make a powerful network with combined functionalities of both cutting-edge technologies. Accordingly, we develop EI-chain and Chain-intelligence to realize reliable computing-power management, data administration, and model optimization at the edges, while improving the functions of BC by leveraging complementary characteristics of EI and BC, further making up for their own limitations. In this survey, a wide spectrum of literature is carefully reviewed to enable the EI-chain and Chain-intelligence. Moreover, we cover the technological aspects of EI-chain and Chain-intelligence: overview, motivations, and frameworks. Finally, some challenges and future directions are explored. We believe this survey will provide developers and researchers a comprehensive view on the synergy of EI and BC, while accelerating the design of a powerful integrated network.

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SoliAudit: Smart Contract Vulnerability Assessment Based on Machine Learning and Fuzz Testing

Cited by 89 publications

References 4 publications

Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work

Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work

A survey: Making “Smart Contracts” really smart

Synergy of Edge Intelligence and Blockchain: A Comprehensive Survey

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