Meta Uses AI to Analyze Clusters of Privacy Incidents as it Seeks Systemic Issues
SANTA CLARA, Calif. -- Meta is taking a more proactive approach to preventing systemic privacy incidents, said Sam Havron, a privacy engineer on Meta’s incident management team.
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"Privacy incidents can share similar root causes or outcomes, and these systemic incidents can emerge due to gaps in the standard incident management process that's generally focused on individual incident handling,” Havron said at the USENIX Privacy Engineering Practice and Respect (PEPR) conference Monday.
To address this, Meta adopted a process that includes identifying clusters of privacy incidents, analyzing each cluster to identify patterns, remediating problems and automatically detecting regressions when new incidents occur, he said. The company uses large language models as part of the process.
"Continuously clustering and raising the visibility of related incidents is critical to enabling comprehensive root cause pattern analysis and designing better remediations that are durable over time and validated through regression monitoring,” said Havron. “This is where building automation and structure can have a huge impact on the quality and consistency of preventing systemic incidents."