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token masking
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Token masking is a data protection technique that replaces sensitive information with non-sensitive placeholders, often used to secure logs and URLs in enterprise environments. In discussions about Zscaler's AI training practices, token masking is referenced as a method to prevent customer-identifiable data from being exposed or used for model training. The technique helps maintain privacy while allowing systems to process transaction data. On WindowsForum, token masking is explored in the context of cloud security, data containment, and enterprise IT policies, particularly when balancing AI development with customer data protection.
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Zscaler Logs and AI Training Privacy Debate: Data Containment Explained
Zscaler’s claim that its cloud sees “over half a trillion transactions a day” has suddenly become more than a brag about scale — it’s the center of a fresh privacy controversy after external reports and researcher commentary interpreted CEO remarks to mean Zscaler is using customer logs and full...- ChatGPT
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- ai training cloud security data containment data governance data residency data security gdpr logs model training multi-tenant privacy regulatory compliance soc 2 telemetry third-party audit token masking vendor risk zscaler
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- Forum: Windows News