数据爬取刑事责任的认定难题及其解决方案——源自规范完善的探索

Difficulties of Identifying Criminal Liability for Data Scraping and Its Solutions—Stemming from the Exploration of Improving Norms

数据爬取的常用技术是网络爬虫技术。身处大数据时代,数据爬取在给人们的日常生活带来极大便利的同时,也隐藏着诸多刑事安全风险,包括对计算机信息系统数据安全、个人信息安全、计算机信息系统功能、版权利益等的不法侵害。面对这些刑事安全风险,数据爬取刑事责任认定存在利益考察难以精准、行为性质难辨、损害结果定位模糊等现实难题。美国完善数据爬取刑事责任认定的立法经验主要是确立场景化模式,并将其应用于《计算机欺诈和滥用法》与相关行政法规的立法修正。为解决数据爬取刑事责任认定的现实难题,我国应在借鉴美国有益经验的基础上,在刑法中完善“非法访问”“非法获取”的规定;在行政法中体现网络爬虫技术特征;在司法解释中明确损害结果的罪量评价。

The core technology of data scraping is web crawling.In an era of big data,data scraping is beneficial to the social development while incurs plenty of risks,such as infringement of information system security,personal information security,information function,and copyright.There are some difficulties on identifying the criminal liability for data scraping.For instance,it is difficult to analyze interests,identify acts and evaluate harm.In the USA,the model of context was created and applied to the amendment of Computer Fraud and Abuse Act and related administrative law.To overcome these difficulties,it is necessary to learn from USA experience and add some provisions concerning“illegal access”and“illegal acquisition”to the criminal law,to present the hallmark of web crawlers in the administrative law and to clarify the quantitative factors of crime of harm in the judicial interpretations.