个人数据分类

An Important Foundation For Security, Privacy, and Compliance at Airbnb

在Airbnb中,执行解决方案对于安全、隐私和合规性至关重要。

By: Sam Kim, Alex Klimov, Woody Zhou, Sylvia Tomiyama, Aniket Arondekar, Ansuman Acharya

作者:Sam KimAlex KlimovWoody ZhouSylvia TomiyamaAniket ArondekarAnsuman Acharya

Introduction

介绍

Airbnb is built on trust. One key way we maintain trust with our community is by ensuring that personal data is handled with care, in a manner that meets security, privacy, and compliance requirements. Understanding where and what personal data exists is foundational to this.

Airbnb建立在信任之上。我们与社区保持信任的一个关键方式是确保个人数据得到谨慎处理,以满足安全、隐私和合规性要求。了解个人数据的存在位置和内容是这一基础。

Over the past several years, we’ve built our own data classification system that adapts to the needs of our data ecosystem, to streamline our processes, and further unlock our ability to protect the data entrusted to Airbnb. This was made possible by many teams working closely to achieve this overarching, shared objective. Information Security, Privacy, Data Governance, Legal, and Engineering collaborated to tackle this problem holistically to produce a unified data identification and classification strategy across all data stores.

在过去的几年中,我们建立了自己的数据分类系统,以适应我们数据生态系统的需求,以简化我们的流程,并进一步释放我们保护Airbnb委托的数据的能力。这得益于许多团队的紧密合作,共同努力实现这个总体目标。信息安全、隐私、数据治理、法务和工程部门合作解决这个问题,以在所有数据存储中产生统一的数据识别和分类策略。

In this blog, we will shed light on the complexities of how data classification works at Airbnb, what measurements we set to assess the quality, performance, and accuracy of the systems involved, and the important considerations when building a data classification system. We hope to share insights for others that are facing similar challenges and to provide a framework for how data classification systems can be built at scale.

在这篇博客中,我们将揭示Airbnb数据分类工作的复杂性,我们设置的衡量系统质量、性能和准确性的指标,以及构建数据分类系统时需要考虑的重要因素。我们希望为面临类似挑战的其他人分享见解,并为如何构建大规模的数据分类系统提供一个框架。

The Complexities of Data Classification at Airbnb

在Airbnb的数据分类复杂性

Data classification is the process of identifying where data exists and then organizing, detecting...

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