基于制度信任构建用户大数据隐私制度保护体系

Building User Big Data Privacy Protection System Based on Institutional Trust

自2012年提出大数据以来,大数据在国家战略层面和组织运营方面得到飞速发展。海量数据的收集、组织与分析能够促进商业组织和非营利组织更好地了解用户和服务对象,在用户主动登记注册和组织主动搜集双方面推动下,关乎用户的人口、地理、消费行为、生活点滴,甚至微妙的心理变化等各领域的大数据被上升到研究分析层面,但同时用户个人隐私也遭受不同程度的侵害,引发大数据隐私保护问题。目前在法律和技术共同管理的情况下,存在制度保护缺位,建议从易位保护用户大数据隐私的主体、以用户隐私泄露容忍度为基准建立大数据动态隐私边界、建立第三方问责制度3个方面构建多维制度保护体系,增加服务主体泄露成本,提高大数据隐私保护力度。

Since big data was put forward in 2012, big data has developed rapidly at the national strategic level and organization operation. The collection, organization, and analysis of massive data can promote commercial organizations and non-profit organizations to better understand users and service objects. It is driven by the active registration of users and the active collection of organizations. It is related to the population, geography, consumer behavior, and life of users. Bits, even subtle psychological changes and other big data in various fields have been raised to the level of research and analysis. While the technology cheers, users＇ personal privacy suffers varying degrees of infringement, triggering the issue of big data privacy protection. In the current situation of legal and technical joint management, there is a lack of institutional protection. It is recommended to protect the privacy of users from the privacy of the user, establish a big data dynamic privacy boundary based on user privacy leakage tolerance, and establish a big data life cycle protection. The system and the establishment of a third-party article system form a multi- dimensional system protection system in four aspects, increase the disclosure cost of service subjects, and improve the protection of big data privacy.