Solidity Programming Language Research Articles

Automation and smart materials in detecting smart contracts vulnerabilities in Blockchain using deep learning

Smart contracts are a vital component of applications being built by blockchain or distributed ledger technology. Smart contracts consists of computer code that composed set of rules agreed upon by the involved parties. When these predefined conditions or rules are satisfied by the transactions initiated by parties, the smart contract executes itself to complete the transaction. Normally, while performing transactions with agreements involving multiple parties, a third party have to be involve to verify all the information, which makes it complex and time consuming process. Smart contracts simplify this process by eliminating the third party and automating the process, enabling the stakeholders to perform transactions directly with each other. Smart contract itself is replicated among multiple nodes of a blockchain there by giving benefits of immutability, security and permanence. Most smart contracts are written in Solidity programming language due to its simplicity and conciseness. Attackers are attracted by the popularity of Solidity language and its vulnerability possibilities. For example, in the 2016 year, 60 million US dollars was theft by Decentralized Autonomous Organization (DAO) attack due to vulnerabilities present in smart contracts. There are few existing tools and papers on this area to find vulnerabilities on smart contracts but taking more time to predict. Thus, this paper presents different Deep learning techniques with satisfactory results to identify smart contract vulnerabilities which are Re-entrancy, Denial of Service (DOS) and Transaction Origin using binary, multi class and multi label classification techniques.

Implementation of a Secure Ride-Sharing DApp Using Smart Contracts on Ethereum Blockchain

The idea of sharing economy gives rise to unique ideas and develops innovative businesses. This article aims to relate the smart city concept by introducing the smart transport system and explores the opportunities of adopting blockchain technology in ride-sharing services. Blockchain technology is a distributed, decentralized public ledger that allows peer-to-peer transactions in a secured way without any third party. This paper proposes a blockchain-based framework from the existing centralized framework for a ride-sharing service and implements the same as a decentralized application (DApp) based on smart contracts on Ethereum Blockchain. Using smart contracts facilitate the users with automated transactions, removes the intermediaries, and enables various activities to be carried out safely and securely. Implementation of smart contracts is done using the Solidity programming language. This DApp uses the min matching algorithm to match riders requesting rideshare to save total travel distance. With the overwhelming growth in the usage of cryptocurrencies, smart contracts usage in applications as proposed in this paper can transform the sharing economy.

Blockchain-based Preferential E-Voting System DApp using Smart Contract

For long, different e-voting systems have been provided with the goal of increasing security and minimizing cost. Blockchain is a major breakthrough in the technological industry that provide immense secured platform. With the launch of Ethereum, a decentralized platform which runs decentralized applications (DApps) on it, a secured voting system now seems possible. Many organizations have now shifted their focus on voting through blockchain platforms. There’s a very high chance that a normal voting method won’t lead to a clear majority. There can be many ways to deal with this issue which includes another voting process to take place which can be quite expensive in terms of time and resources. In our paper, we introduce the vote-trading concept where the votes can be redistributed to other candidates in case if there is no clear majority and also this ‘ majority’ factor can be set by the organization according to their requirement. We discuss the design for the blockchain based preferential e-voting system using the Solidity programming language where instead of one vote per candidate, we provide the concept of giving preference to the candidates.

A self-sovereign identity management scheme using smart contracts

The existing self-sovereign identity management schemes have some problems, such as weak availability and security risks. To solve these problems, we proposed a cross-domain self-sovereign identity management scheme using smart contracts. This scheme takes into account the entire lifecycle of identity, especially including the cross-domain use and recovery. To preserve the privacy data of users on the blockchain, we proposed a data storage method of anchoring on blockchain. Finally, we implemented this scheme using the Solidity programming language for smart contract. This scheme has been experimentally verified to be capable of maintaining the expenditure of resources under control and having good usability. Compared with other self-sovereign identity management schemes, this scheme has better performance in terms of controllability, security and portability.

Solidity : Smart Contract Language or Legal Contract Language

This article primarily focuses on how to set up a smart contract with Solidity. Considering that the usage and examples of smart contracts are increasing day by day, the number of contracts written with Solidity is increasing at the same rate. These contracts, in which computers describe the will of the parties in codes, have a relieving effect for the legal sector as well. Although “language” is the basis of the law, smart contracts are perfect for contracts that can be put forward concretely without human emotions. In this article, I started by defining what a smart contract is. Based on the definition of smart contract, I wrote in which sectors and in which projects smart contracts are used. Finally, I introduced the Solidity programming language, which is the main purpose of this article, and I wrote and explained the Inheritance Contract with Solidity.

Lolisa: Formal Syntax and Semantics for a Subset of the Solidity Programming Language in Mathematical Tool Coq

The security of blockchain smart contracts is one of the most emerging issues of the greatest interest for researchers. This article presents an intermediate specification language for the formal verification of Ethereum-based smart contract in Coq, denoted as Lolisa. The formal syntax and semantics of Lolisa contain a large subset of the Solidity programming language developed for the Ethereum blockchain platform. To enhance type safety, the formal syntax of Lolisa adopts a stronger static type system than Solidity. In addition, Lolisa includes a large subset of Solidity syntax components as well as general-purpose programming language features. Therefore, Solidity programs can be directly translated into Lolisa with line-by-line correspondence. Lolisa is inherently generalizable and can be extended to express other programming languages. Finally, the syntax and semantics of Lolisa have been encapsulated as an interpreter in mathematical tool Coq. Hence, smart contracts written in Lolisa can be symbolically executed and verified in Coq.

A Hybrid Formal Verification System in Coq for Ensuring the Reliability and Security of Ethereum-Based Service Smart Contracts

This paper reports a formal symbolic process virtual machine (FSPVM) denoted as FSPVM-E for verifying the reliability and security of Ethereum-based services at the source code level of smart contracts. A Coq proof assistant is employed for programming the system and for proving its correctness. The current version of FSPVM-E adopts execution-verification isomorphism, which is an application extension of Curry-Howard isomorphism, as its fundamental theoretical framework to combine symbolic execution and higher-order logic theorem proving. The four primary components of FSPVM-E include a general, extensible, and reusable formal memory framework, an extensible and universal formal intermediate programming language denoted as Lolisa, which is a large subset of the Solidity programming language using generalized algebraic datatypes, the corresponding formally verified interpreter of Lolisa, denoted as FEther, and assistant tools and libraries. The self-correctness of all components is certified in Coq. FSPVM-E supports the ERC20 token standard, and can automatically and symbolically execute Ethereum-based smart contracts, scan their standard vulnerabilities, and verify their reliability and security properties with Hoare-style logic in Coq.

Debugging Smart Contract’s Business Logic Using Symbolic Model Checking

Smart contracts are a special type of programs running inside a blockchain. Immutable and transparent, they provide means to implement fault-tolerant and censorship-resistant services. Unfortunately, its immutability causes a serious challenge of ensuring that a business logic and implementation is correct upfront, before publishing in a blockchain. Several big accidents have indeed shown that users of this technology need special tools to verify smart contract correctness. Existing automated checkers are able to detect only well known implementation bugs, leaving the question of business logic correctness far aside. In this work, we present a symbolic model-checking technique along with a formal specification method for a subset of Solidity programming language that is able to express both state properties and trace properties; the latter constitutes a weak analogy of temporal properties. We evaluate the proposed technique on the MiniDAO smart contract, a young brother of notorious TheDAO. Our Proof-of-Concept was able to detect a non-trivial error in the business logic of this smart contract in a few seconds.

Implementation of Blockchain Technology in Education System

The Blockchain for Education platform helps us to make the tamper-proof certificates and their correct and the overall permanent allocation of these certificates to learners, as well as verification of certificates. It can reduce the overall frauds and tampering of the degrees and certificates. Blockchain technology can be used to solve many educational problems and can help educators as well as learners to monitor the learning outcomes. The data can be stored securely and tamper proof format when it’s stored onto the blockchain network. Here smart contracts can be designed and deployed on to the Ethereum blockchain that can be designed using the solidity programming language. Blockchain can be applied to private, public and consortium sectors depending upon the usage and the scope of the blockchain. Education system can take benefit of this scalability of the blockchain and can be effectively useful in the educational institutions.

Blockchain: A Tale of Two Applications

Bitcoin continues to get more and more attention from the media, mainly because of the volatility of its value and insignificantly associated with the technological innovation. This cryptocurrency is supported by an immutable database and is distributed throughout a network of thousands of nodes, known as Blockchain. One way to ensure that all the concepts behind the Blockchain technology and infrastructure are seized is to conduct the development of one of the most popular context applications for it: a wallet for well-known cryptocurrencies. Yet Another Bitcoin Wallet (YABW) is a hybrid application available for both Android and iOS, which was developed with the Ionic and Angular frameworks. This application communicates with Bitcoin Blockchain to send, receive and store bitcoins; provides a set of features focused on security and user experience, and is available on the Play Store and Apple Store. A rather relevant issue that is becoming a major subject of current research is the application of the Blockchain infrastructure to other contexts that are neither directly connected to cryptocurrencies, nor are finance related. The implementation of a proof-of-concept application proposes the use of a blockchain for a specific case study: the exchange of meal vouchers of an institution amongst students. This is achieved using the decentralized platform Ethereum, which allows us to create a Smart Contract using the Solidity programming language to create a token that follows the Ethereum Request for Comment (ERC), the ERC-20 standard and represents the meal vouchers. This second application uses the architecture defined for YABW, reusing major components and custom developing specific modules to enhance the required features. There is still a lot of research to be done on the non-financial applicability of the Blockchain infrastructure and technology, but for the moment, we have left further evidence that it is possible and is a relative straight-forward process to accomplish from the technological perspective.

Formal Process Virtual Machine for Smart Contracts Verification

This paper reports on the development and verification of a novel formal symbolic process virtual machine (FSPVM) for verifying the reliability and security of Ethereum smart contracts, denoted as FSPVM-E, completely in Coq proof assistant. It adopts execution-verification isomorphism (EVI), an extension of Curry-Howard isomorphism (CHI), as its fundamental theoretical framework. The current version of FSPVM-E is constructed on a general, extensible, and reusable formal memory (GERM) framework, an extensible and universal formal intermediate programming language Lolisa, which is a large subset of the Solidity programming language using generalized algebraic datatypes, and the corresponding formally verified interpreter of Lolisa, denoted as FEther. It supports the ERC20 standard and can automatically simultaneously symbolically execute the smart contract programs of Ethereum and verify their reliability and security properties using Hoare logic in Coq. In addition, this work, contributes to solving the problems of automation, inconsistency and reusability in higher-order logic theorem proving.

Optimization of Executable Formal Interpreters Developed in Higher-Order Logic Theorem Proving Systems

In recent publications, we presented a novel formal symbolic process virtual machine (FSPVM) framework that combined higher-order theorem proving and symbolic execution for verifying the reliability and security of smart contracts developed in the Ethereum blockchain system without suffering the standard issues surrounding reusability, consistency, and automation. A specific FSPVM, denoted as FSPVM-E, was developed in Coq based on a general, extensible, and reusable formal memory (GERM) framework, an extensible and universal formal intermediate programming language, denoted as Lolisa, which is a large subset of the Solidity programming language that uses generalized algebraic datatypes, and a corresponding formally verified interpreter for Lolisa, denoted as FEther, which serves as a crucial component of FSPVM-E. However, our past work has demonstrated that the execution efficiency of the standard development of FEther is extremely low. As a result, FSPVM-E fails to achieve its expected verification effect. The present work addresses this issue by first identifying three root causes of the low execution efficiency of formal interpreters. We then build abstract models of these causes, and present respective optimization schemes for rectifying the identified conditions. Finally, we apply these optimization schemes to FEther, and demonstrate that its execution efficiency has been improved significantly.

Automation of the supplier role in the GB power system using blockchain-based smart contracts

An electricity supply smart contract was developed and demonstrated to perform pre-time-of-use price negotiation between demand and generation and posttime- of-use settlement and payment. The smart contract was demonstrated with 1000 loads/generators with usages simulated using lognormal probability distributions. It combines payment of deposit, negotiation of price based on estimates, settlement based on actual usage and enactment of payments using crypto-currency. The settlement procedure rewards customers that adjusted to balance the system. The smart contract was written in the Solidity programming language and implemented with a simulated Ethereum blockchain using testrpc and go-ethereum. In the example test case, a price was agreed, settled and payment enacted.