基于语义嵌入模型与交易信息的智能合约自动分类系统  

Towards Automatic Smart-contract Codes Classification by Means of Word Embedding Model and Transaction Information

作　　者：黄步添 刘琦 何钦铭[1] 刘振广 陈建海[1] 

机构地区：[1]浙江大学计算机科学与技术学院 [2]杭州云象网络技术有限公司 [3]新加坡国立大学计算机学院

出　　处：《自动化学报》2017年第9期1532-1543,共12页Acta Automatica Sinica

摘　　要：作为区块链技术的一个突破性扩展,智能合约允许用户在区块链上实现个性化的代码逻辑从而使得区块链技术更加的简单易用.在智能合约代码信息迅速增长的背景下,如何管理和组织海量智能合约代码变得更具挑战性.基于人工智能技术的代码分类系统能根据代码的文本信息自动分门别类,从而更好地帮助人们管理和组织代码的信息.本文以Ethereum平台上的智能合约为例,鉴于词嵌入模型可以捕获代码的语义信息,提出一种基于词嵌入模型的智能合约分类系统.另外,每一个智能合约都关联着一系列交易,我们又通过智能合约的交易信息来更深入地了解智能合约的逻辑行为.据我们所知,本文是对智能合约代码自动分类问题的首次研究尝试.测试结果显示该系统具有较为令人满意的分类性能.As an innovative extension of the blockchain technology, smart contract enables users to implement person- alized logic. As such, blockchain technology becomes more simple and useful. However, due to the rapid increase of the amount of smart contract codes, managing smart contract codes is becoming much more challenging. Automatic code classifier, which rests on the machine learning methods, can automatically identify the categories of the codes so as to saves a lot of human efforts. In this paper we investigate the smart contract codes of the Ethereum platform and propose a novel smart contract code classifier. To the best of our knowledge, this is the first exploration on automatic classification of the smart contract codes. The classifier is based on the word embedding model. Since each smart contract corresponds to a series of transactions, we further utilize the transactions in the contract to understand the intrinsic logic of the contract. Extensive experiments have verified the effectiveness of our proposed system.

关 键 词：智能合约 代码 交易信息 词嵌入模型 神经网络 长短时记忆模型 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] TP391.1[自动化与计算机技术—计算机科学与技术]