Systematic Review of Security Vulnerabilities in Ethereum Blockchain Smart Contract

Kushwaha, Satpal Singh; Joshi, Sandeep; Singh, Dilbag; Kaur, Manjit; Lee, Heung-No

doi:10.1109/access.2021.3140091

Cited by 114 publications

(28 citation statements)

References 126 publications

(108 reference statements)

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“…The sum of the theoretical probability is the probability of randomly finding a basic block and the basic block to be tested in contract 2. The final absolute similarity calculation formula is Equation (8) [71]…”

Section: Methods Calculation Object Equationmentioning

confidence: 99%

See 1 more Smart Citation

Bytecode Similarity Detection of Smart Contract across Optimization Options and Compiler Versions Based on Triplet Network

Zhu¹,

Feng²,

Pang³

et al. 2022

Electronics

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In recent years, the number of smart contracts running in the blockchain has increased rapidly, accompanied by many security problems, such as vulnerability propagation caused by code reuse or vicious transaction caused by malicious contract deployment, for example. Most smart contracts do not publish the source code, but only the bytecode. Based on the research of bytecode similarity of smart contract, smart contract upgrade, vulnerability search and malicious contract analysis can be carried out. The difficulty of bytecode similarity research is that different compilation versions and optimization options lead to the diversification of bytecode of the same source code. This paper presents a solution, including a series of methods to measure the similarity of smart contract bytecode. Starting from the opcode of smart contract, a method of pre-training the basic block sequence of smart contract is proposed, which can embed the basic block vector. Positive samples were obtained by basic block marking, and the negative sampling method is improved. After these works, we put the obtained positive samples, negative samples and basic blocks themselves into the triplet network composed of transformers. Our solution can obtain evaluation results with an accuracy of 97.8%, so that the basic block sequence of optimized and unoptimized options can be transformed into each other. At the same time, the instructions are normalized, and the order of compiled version instructions is normalized. Experiments show that our solution can effectively reduce the bytecode difference caused by optimization options and compiler version, and improve the accuracy by 1.4% compared with the existing work. We provide a data set covering 64 currently used Solidity compilers, including one million basic block pairs extracted from them.

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Section: Methods Calculation Object Equationmentioning

confidence: 99%

“…At the same time, the program complexity of smart contracts and the amount of code per unit contract are also increasing year by year. The code reuse of smart contracts brings more and more serious security problems [8].…”

Section: Introductionmentioning

confidence: 99%

Bytecode Similarity Detection of Smart Contract across Optimization Options and Compiler Versions Based on Triplet Network

Zhu¹,

Feng²,

Pang³

et al. 2022

Electronics

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“…This section explains the survey on various research issues and outcomes on urban flooding, high definition monitoring using a concurrent multipath wireless environment, and the role of IoT and its previous use [ 20 ]. The goal of implementing the techniques is simply to generate early warnings as natural disasters such as floods, rainstorms, tsunamis, and others that pose a major threat to life and property all over the world.…”

Section: Preliminary Studiesmentioning

confidence: 99%

“…IoT use cases are frequently text-intensive with unpredictable traffic surges. If your team is concerned about scalability, document databases like MongoDB or DynamoDB can be excellent solutions for handling system demand [ 20 ]. The provision of advance warning of conditions that are likely to cause flooding of property and a potential risk to life is known as “flood warning.” The primary goal of a flood warning is to save lives by giving people, their support systems, and emergency responders enough time to prepare for flooding.…”

Section: Introductionmentioning

confidence: 99%

Cloud-Based IoE Enabled an Urban Flooding Surveillance System

Dhaya

Ahanger

Asha³

et al. 2022

Computational Intelligence and Neuroscience

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A flood is defined as a surplus of water or sludge on parched soil, and a flood has originated through the runoff of water inside the water route from the various water sources like canals, etc. Intense rainfall, deforestation, urbanization, deprived water and sewerage administration, and lack of concentration toward the environment of the hydrological scheme have been the causes of urban flooding. In addition, there is a deficiency in flood assessment due to the impediment in getting data on floods to the control room from the flood-affected area. To diminish the possessions due to flooding, there ought to be an immediate move of captured statistics as of the hectic region en route to the observation room with no further wait for a completely fledged technique in the wireless settings data from the Internet of Things (IoT). The Internet of Everything (IoE) is a concept that extends the Internet of Things. In view of the fact that the wireless nodes are changeable in their environment, those effects lead to unsteadiness and uncertainty in information distribution. Therefore, there is a requirement for flood-predictable region data that may be exaggerated between the source and the control room. In the past, there were a lot of techniques set up and put into practice intended for keeping an eye on the flood spots. However, one of the biggest challenges is to have data sharing without delay and loss of data among source and destination nodes. In addition to that, the video quality also needs to be taken into consideration at the same time in receipt, as it is a tough task to determine and preplan the flood happenings completely from the normal disaster that makes scientific complicatedness more than the information being received in a wireless ad-hoc environment using IoT-based sensors. Considering all the abovementioned reasons, the proposed work comprises of three folded goals, namely, the design of a mobile ad-hoc flooding environment, the development of an urban flood high definition video surveillance system using IoT-based sensors, and experimental work on simulation.

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“…Generally speaking, blockchain can be divided into two categories: unauthorized blockchain and authorized blockchain [14]. e former category is usually used to build payment systems instead of centralized banks, such as Bitcoin or Ethereum [15,16], and the latter is designed for specific application scenarios such as medical, agrifood, or other fields. No matter what type of blockchain is being used, it can help to build trust between participants in an exchange.…”

Section: Blockchain and Distributed Ledgersmentioning

confidence: 99%

Design of a Blockchain-Based Traceability System with a Privacy-Preserving Scheme of Zero-Knowledge Proof

Xue

2022

Security and Communication Networks

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With the fast development of the industrial Internet, its interconnectivity poses new challenges for the cooperation of industrial entities. Cooperation among these entities is built on trust, and trust is based on high-quality industrial products at reasonable prices. A traceability system can play an essential role in objectively reflecting the production process and promoting this trust. However, traditional traceability systems often have data privacy issues. Because traceability data are collected or generated during the production process (namely, production-related data), they could be considered privacy data. Several researchers have introduced privacy protection schemes into the traceability system, such as authentication or encryption. Nevertheless, when a privacy protection scheme is established, the original data are disclosed to the legal user of the system, but the data may still be leaked intentionally or unintentionally. Except for data privacy issues, a traditional traceability system can be vulnerable to network attacks, data unavailability, and reliability issues. The authors conducted a study to overcome these shortcomings, and this paper reports the results. We built a traceability prototype system using a blockchain protocol and a zero-knowledge proof method. First, we built a blockchain to record key production process data, aiming to maintain data reliability and availability. Second, through an analysis of traceability purpose using production knowledge, the traceability purpose could be divided into multiple provable statements. By introducing privacy protection through a zero-knowledge proof, the traceability process was converted to proving relative statements. Finally, the statements were validated by a smart contract that provided openness and reliability during the traceability process. Analysis has shown that our approach could meet the requirements for high security and privacy. In addition, the paper also discusses the calculation cost of the traceability process to show our work’s viability. The traceability system described in this paper creates new possibilities for constructing a healthy and reliable trust relationship between production entities to provide further support in the development of the industrial Internet.

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Systematic Review of Security Vulnerabilities in Ethereum Blockchain Smart Contract

Cited by 114 publications

References 126 publications

Bytecode Similarity Detection of Smart Contract across Optimization Options and Compiler Versions Based on Triplet Network

Bytecode Similarity Detection of Smart Contract across Optimization Options and Compiler Versions Based on Triplet Network

Cloud-Based IoE Enabled an Urban Flooding Surveillance System

Design of a Blockchain-Based Traceability System with a Privacy-Preserving Scheme of Zero-Knowledge Proof

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