Security Threat Mitigation for Smart Contracts: A Comprehensive Survey

Author:

Ivanov Nikolay1ORCID,Li Chenning1ORCID,Yan Qiben1ORCID,Sun Zhiyuan2ORCID,Cao Zhichao1ORCID,Luo Xiapu2ORCID

Affiliation:

1. Michigan State University, USA

2. The Hong Kong Polytechnic University, Hong Kong

Abstract

The blockchain technology, initially created for cryptocurrency, has been re-purposed for recording state transitions of smart contracts—decentralized applications that can be invoked through external transactions. Smart contracts gained popularity and accrued hundreds of billions of dollars in market capitalization in recent years. Unfortunately, like all other computer programs, smart contracts are prone to security vulnerabilities that have incurred multibillion-dollar damages over the past decade. As a result, many automated threat mitigation solutions have been proposed to counter the security issues of smart contracts. These threat mitigation solutions include various tools and methods that are challenging to compare. This survey develops a comprehensive classification taxonomy of smart contract threat mitigation solutions within five orthogonal dimensions: defense modality, core method, targeted contracts, input-output data mapping, and threat model. We classify 133 existing threat mitigation solutions using our taxonomy and confirm that the proposed five dimensions allow us to concisely and accurately describe any smart contract threat mitigation solution. In addition to learning what the threat mitigation solutions do, we also show how these solutions work by synthesizing their actual designs into a set of uniform workflows corresponding to the eight existing defense core methods. We further create an integrated coverage map for the known smart contract vulnerabilities by the existing threat mitigation solutions. Finally, we perform the evidence-based evolutionary analysis, in which we identify trends and future perspectives of threat mitigation in smart contracts and pinpoint major weaknesses of the existing methodologies. For the convenience of smart contract security developers, auditors, users, and researchers, we deploy and maintain a regularly updated comprehensive open-source online registry of threat mitigation solutions, called Security Threat Mitigation (STM) Registry at https://seit.egr.msu.edu/research/stmregistry/ .

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference190 articles.

1. Sathish Ramani. 2020. Exploring the Methods of Looking into Ethereum’s Transaction Pool (Mempool). Chainstack. Retrieved from https://chainstack.com/exploring-the-methods-of-looking-into-ethereums-transaction-pool/.

2. IBM. 2022. Artificial Intelligence (AI) for Cybersecurity. IBM. Retrieved from https://www.ibm.com/security/artificial-intelligence.

3. Dedaub. 2022. Dedadub Contract Library. Dedaub Ltd. Retrieved from https://dedaub.com/contract-library.

4. block.one. 2022. EOS.IO Technical White Paper v2. GitHub. Retrieved from https://github.com/EOSIO/Documentation/blob/master/TechnicalWhitePaper.md.

5. Etherscan. 2022. Etherscan Token Tracker. Etherscan. Retrieved from https://etherscan.io/tokens.

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exemplary Ethereum Development Strategies Regarding Security and Gas-Saving;Electronics;2023-12-27

2. Analyzing the Threats to Blockchain-Based Self-Sovereign Identities by Conducting a Literature Survey;Applied Sciences;2023-12-22

3. SoliTester: Detecting exploitable external‐risky vulnerability in smart contracts using contract account triggering method;Journal of Software: Evolution and Process;2023-11-10

4. DynamicFL: Balancing Communication Dynamics and Client Manipulation for Federated Learning;2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON);2023-09-11

5. Graph-based Analysis of the Algorand Blockchain Network;2023 International Conference on Blockchain Technology and Information Security (ICBCTIS);2023-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3