针对生成式人工智能大模型攻击行为的刑法规制研究OA
Research on criminal law response to attacks against large GenAI models
针对生成式人工智能大模型的攻击行为亟须刑法回应.刑法适用存在评价困境:训练数据难以评价为计算机信息系统数据;无系统功能损害的数据变更行为遗漏评价;对模型的窃取攻击难以评价为非法控制行为;输出偏差难以评价为计算机系统不能正常运行.立足解释论路径激活既有刑法规范,扩大解释"计算机信息系统中的数据",重新阐释系统犯罪内涵,重构破坏型犯罪结果维度,由此实现对攻击行为的全面规制.
There is an urgent need for a criminal law response to attacks against large Generative AI(GenAI)models.The application of criminal law faces evaluative challenges:it is difficult to classify training data as data within a computer information system;alterations to data that do not impair system functionality are often overlooked in evaluations;attacks involving the theft of models are difficult to classify as acts of unlawful control;and output biases are difficult to classify as causing a computer system to malfunction.By adopting an interpretive approach to revitalize existing criminal law provisions,expanding the interpretation of"data in computer information systems,"reinterpreting the essence of"system crime",and reconstructing the dimension of consequences in destructive crimes,we can thereby achieve comprehensive regulation of attack-related conduct.
黄洁
安徽大学法学院,合肥 230601
社会科学
数据安全非法获取计算机信息系统数据罪非法控制计算机信息系统罪破坏计算机信息系统罪扩大解释
data securitycrime of illegally obtaining computer information system datacrime of illegally controlling computer information systemcrime of damaging computer information systemexpansive interpretation
《信息通信技术与政策》 2026 (8)
45-51,7
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