USENIX Security2022Top-tier venue
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
Abstract
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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Install the CLIlune papers fulltext 9e6c3d48-8534-4297-85bb-244f3e01dfc8Cited by top-tier papers13
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