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USENIX Security2022顶会

PrivGuard: Privacy Regulation Compliance Made Easier

Lun Wang, Usmann Khan, Joseph P. Near, Qi Pang, Jithendaraa Subramanian, Neel Somani, Peng Gao, Andrew Low, Dawn Song

出版方
2022年份
13顶会引用

摘要

Continuous compliance with privacy regulations, such as GDPR and CCPA, has become a costly burden for companies from small-sized start-ups to business giants. The culprit is the heavy reliance on human auditing in today's compliance process, which is expensive, slow, and errorprone. To address the issue, we propose PRIVGUARD, a novel system design that reduces human participation required and improves the productivity of the compliance process. PRIVGUARD is mainly comprised of two components: (1) PRIVANALYZER, a static analyzer based on abstract interpretation for partly enforcing privacy regulations, and (2) a set of components providing strong security protection on the data throughout its life cycle. To validate the effectiveness of this approach, we prototype PRIVGUARD and integrate it into an industrial-level data governance platform. Our case studies and evaluation show that PRIVGUARD can correctly enforce the encoded privacy policies on real-world programs with reasonable performance overhead.

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