Solidifier

Antonino, Pedro; Roscoe, A. W.

doi:10.1145/3412841.3442051

Cited by 13 publications

(13 citation statements)

References 22 publications

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“…Formal analysis methods convert a smart contract into a formal representation and run a solver over this representation to prove or disprove some security properties. Most solutions employing the formal analysis core method belong to either the prevention defense modality (e.g., Lolisa [166], Model-Checking [122], Li et al [101], Solidifier [28], VeriSol [160]) or the exploration modality (e.g., KEVM [83], Grishchenko et al [77]). However, SeRIF [47], which primary purpose is defense against reentrancy, demonstrates that the formal analysis can also be used for targeting vulnerabilities.…”

Section: Core Methodsmentioning

confidence: 99%

Security Threat Mitigation For Smart Contracts: A Survey

Иванов¹,

Li²,

Sun³

et al. 2023

Preprint

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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 programs, smart contracts are prone to security vulnerabilities that have incurred multimillion-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 a regularly updated comprehensive open-source online registry of threat mitigation solutions.CCS Concepts: • Security and privacy → Distributed systems security.

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Section: Core Methodsmentioning

confidence: 99%

Security Threat Mitigation For Smart Contracts: A Survey

Иванов¹,

Li²,

Sun³

et al. 2023

Preprint

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“…We use the term social game to denote a class of smart contracts that govern the participation and interaction of several users, in accordance with a set of predefined rules. Examples of social games comprise voting schemes [27], auctions [262,205,285,66,27], lotteries [66], as well as various games including gambling [14,100,160],…”

Section: Social Gamesmentioning

confidence: 99%

“…Social games usually ask each user to accompany their submission with a participation fee, with submissions ranging from a ballot vote [51], an auction bid [262,66,27],…”

Section: Social Gamesmentioning

confidence: 99%

“…These tools are often automated [297,103,259,273] and can identify multi-transaction, i.e., composite, vulnerabilities [60] as well as analyze a smart contract from the point of its semantic correctness [310]. However, program verification, and static analysis in particular, can be challenging as it requires precise abstraction of a contract's execution and memory model [259,27,137], which can be unsound [259].…”

Section: Program Verificationmentioning

confidence: 99%

“…Many static analysis techniques do not consider the gas mechanism of Ethereum smart contract execution [27,259,160], while some others focus specifically on estimating gas consumption [16,204].…”

Section: Program Verificationmentioning

confidence: 99%

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Securing smart contracts with formal verification and automated program repair

Tolmach¹

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had provided me with guidance, encouragement, but also a lot of freedom and resources to explore possible research directions for me to find those I was particulary excited about. I also learned a lot from him, as well as his never-ending energy, enthusiasm, and positive attitude.I also want to thank my co-supervisor Dr Wei Qingsong for his support, encouragement, valuable advice, and help with so many aspects of my PhD. I am immensely indebted to Dr Li Zengxiang who introduced me to academia, research, and blockchain, and helped me start my PhD in Singapore. I am grateful to A*STAR for supporting my PhD, financially and otherwise. I am extremely lucky to have Prof Li Yi and Prof Lin Shang-Wei as my collaborators and mentors, and would like to thank them for their continuous support, insightful research advice, editing my writing, and so much more. Their contributions to this work are invaluable. I would also like to express my appreciation to my wonderful labmates, especially Mr Liu Ye for fruitful research discussions and collaboration. I would also like to extend my gratitude to my friends outside of CSL, particularly Ayana Aspembitova, for their kindness, support, and good example they set for me. I thank my parents, Ihar and Natallia, and my sister Anna for their unparalleled love, endless support, and understanding. Finally, thanks to my husband, Vasily, for being there for me throughout these years. I would have never done it without your support and help. vii Contents Statement of Originality ii

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