算法商业秘密的秘密性认定标准研究

摘要：

算法作为商业秘密的保护客体已经在实证法上得到了确认，但是算法和其他一般的商业秘密相比存在着特殊性，算法秘密性与算法披露规则存在着一定程度的不兼容性，算法的黑箱性与复杂性使得其秘密性认定存在一定障碍。因此有必要对算法商业秘密的秘密性认定标准进行明确，有效落实对算法的商业秘密保护。本文将考虑到算法的特殊性以及《反不正当竞争法》第三十二条在司法适用上存在的问题，并结合相关案例提出相应的优化路径，明确算法秘密性认定标准，对《反不正当竞争法》第三十二条进行合理解释及具体适用。

Abstract:

Algorithm as trade secret protection object has been confirmed in the empirical law, but algorithm has its own characteristics compared to other general trade secrets, there is a certain degree of incompatibility between algorithm secrecy and algorithm disclosure rules. The black box and complexity of algorithm make it difficult to determine its secrecy. Therefore, it is necessary to clarify the standard for determining the secrecy of algorithmic trade secrets, so as to effectively protect algorithmic trade secrets. This paper takes into account the special characteristics of algorithms and the problems in the judicial application of Article 32 of the Anti-Unfair Competition Law, and puts forward corresponding optimization paths in combination with relevant cases, to clarify the standard for the determination of algorithmic secrecy, and provide a reasonable interpretation of Article 32 of the Anti-Unfair Competition Law and its specific application.

基金项目：本文系浙江省高校重大人文社科攻关计划项目资助的规划重点项目“算法商业秘密的法律治理体系研究”（项目编号：2023GH077）的阶段性研究成果。

作者简介：萧静，硕士研究生，研究方向为知识产权法。彭飞荣，通信作者，法学博士，中国计量大学法学院（知识产权学院）教授，国家知识产权培训（浙江）基地副主任，研究方向为知识产权法、标准化法。