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Register a new userA survey on efficient parallelization of blockchain-based smart contracts
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Added by
Alessio Meneghetti
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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The main problem faced by smart contract platforms is the amount of time and computational power required to reach consensus. In a classical blockchain model, each operation is in fact performed by each node, both to update the status and to validate the results of the calculations performed by others. In this short survey we sketch some state-of-the-art approaches to obtain an efficient and scalable computation of smart contracts. Particular emphasis is given to sharding, a promising method that allows parallelization and therefore a more efficient management of the computational resources of the network.
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In this paper we discuss how conventional business contracts can be converted into smart contracts---their electronic equivalents that can be used to systematically monitor and enforce contractual rights, obligations and prohibitions at run time. We explain that emerging blockchain technology is certainly a promising platform for implementing smart contracts but argue that there is a large class of applications, where blockchain is inadequate due to performance, scalability, and consistency requirements, and also due to language expressiveness and cost issues that are hard to solve. We explain that in some situations a centralised approach that does not rely on blockchain is a better alternative due to its simplicity, scalability, and performance. We suggest that in applications where decentralisation and transparency are essential, developers can advantageously combine the two approaches into hybrid solutions where some operations are enforced by enforcers deployed on--blockchains and the rest by enforcers deployed on trusted third parties.
Currently, blockchain proposals are being adopted to solve security issues, such as data integrity, resilience, and non-repudiation. To improve certain aspects, e.g., energy consumption and latency, of traditional blockchains, different architectures, algorithms, and data management methods have been recently proposed. For example, appendable-block blockchain uses a different data structure designed to reduce latency in block and transaction insertion. It is especially applicable in domains such as Internet of Things (IoT), where both latency and energy are key concerns. However, the lack of some features available to other blockchains, such as Smart Contracts, limits the application of this model. To solve this, in this work, we propose the use of Smart Contracts in appendable-block blockchain through a new model called context-based appendable-block blockchain. This model also allows the execution of multiple smart contracts in parallel, featuring high performance in parallel computing scenarios. Furthermore, we present an implementation for the context-based appendable-block blockchain using an Ethereum Virtual Machine (EVM). Finally, we execute this implementation in four different testbed. The results demonstrated a performance improvement for parallel processing of smart contracts when using the proposed model.
Smart Contracts (SCs) in Ethereum can automate tasks and provide different functionalities to a user. Such automation is enabled by the `Turing-complete nature of the programming language (Solidity) in which SCs are written. This also opens up different vulnerabilities and bugs in SCs that malicious actors exploit to carry out malicious or illegal activities on the cryptocurrency platform. In this work, we study the correlation between malicious activities and the vulnerabilities present in SCs and find that some malicious activities are correlated with certain types of vulnerabilities. We then develop and study the feasibility of a scoring mechanism that corresponds to the severity of the vulnerabilities present in SCs to determine if it is a relevant feature to identify suspicious SCs. We analyze the utility of severity score towards detection of suspicious SCs using unsupervised machine learning (ML) algorithms across different temporal granularities and identify behavioral changes. In our experiments with on-chain SCs, we were able to find a total of 1094 benign SCs across different granularities which behave similar to malicious SCs, with the inclusion of the smart contract vulnerability scores in the feature set.
The emerging Internet of Things (IoT) is facing significant scalability and security challenges. On the one hand, IoT devices are weak and need external assistance. Edge computing provides a promising direction addressing the deficiency of centralized cloud computing in scaling massive number of devices. On the other hand, IoT devices are also relatively vulnerable facing malicious hackers due to resource constraints. The emerging blockchain and smart contracts technologies bring a series of new security features for IoT and edge computing. In this paper, to address the challenges, we design and prototype an edge-IoT framework named EdgeChain based on blockchain and smart contracts. The core idea is to integrate a permissioned blockchain and the internal currency or coin system to link the edge cloud resource pool with each IoT device account and resource usage, and hence behavior of the IoT devices. EdgeChain uses a credit-based resource management system to control how much resource IoT devices can obtain from edge servers, based on pre-defined rules on priority, application types and past behaviors. Smart contracts are used to enforce the rules and policies to regulate the IoT device behavior in a non-deniable and automated manner. All the IoT activities and transactions are recorded into blockchain for secure data logging and auditing. We implement an EdgeChain prototype and conduct extensive experiments to evaluate the ideas. The results show that while gaining the security benefits of blockchain and smart contracts, the cost of integrating them into EdgeChain is within a reasonable and acceptable range.
We argue that there is a hierarchy of levels describing to that particular level relevant features of reality behind the content and behavior of blockchain and smart contracts in their realistic deployment. Choice, design, audit and legal control of these systems could be more informed, easier and raised to a higher level, if research on foundations of these descriptions develops and sets the formalisms, tools and standards for such descriptions.
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