[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-08-19。"],[],[],null,["# Using Sensitive Data Protection with Cloud Storage\n\n\u003cbr /\u003e\n\nThis page contains references to pages that provide information on how\nto use Sensitive Data Protection with [Cloud Storage](/storage).\n\nQuickstart guides\n-----------------\n\n[Quickstart: Scheduling an inspection scan](/sensitive-data-protection/docs/schedule-inspection-scan)\n: Schedule periodic inspection of a\n Cloud Storage bucket, a BigQuery table, or a\n Datastore kind. For detailed instructions, see\n [Creating and scheduling inspection jobs](/sensitive-data-protection/docs/creating-job-triggers).\n\nHow-to guides\n-------------\n\nThis section provides a categorized list of task-based guides that demonstrate\nhow to use Sensitive Data Protection with Cloud Storage.\n\n### Inspection\n\n[Inspecting storage and databases for sensitive data](/sensitive-data-protection/docs/inspecting-storage)\n: Create a one-time job that searches for sensitive data in a Cloud Storage\n bucket, a BigQuery table, or a Datastore kind.\n\n[Creating and scheduling inspection jobs](/sensitive-data-protection/docs/creating-job-triggers)\n: Create and schedule a job trigger that searches for sensitive data in a\n Cloud Storage bucket, a BigQuery table, or a\n Datastore kind. A job trigger automates the creation of\n Sensitive Data Protection jobs on a periodic basis.\n\n### Working with scan results\n\n[Sending Sensitive Data Protection scan results to Security Command Center](/sensitive-data-protection/docs/sending-results-to-scc)\n: Scan a Cloud Storage bucket, a BigQuery table, or a\n Datastore kind, and then send the findings to Security Command Center.\n\n[Analyzing and reporting on Sensitive Data Protection findings](/sensitive-data-protection/docs/analyzing-and-reporting)\n: Use Cloud Storage to run analytics on Sensitive Data Protection\n findings.\n\nTutorials\n---------\n\n[De-identification and re-identification of PII in large-scale datasets using Sensitive Data Protection](/architecture/de-identification-re-identification-pii-using-cloud-dlp)\n: Create an automated data transformation pipeline to de-identify sensitive data\n like personally identifiable information (PII).\n\n[Automating the classification of data uploaded to Cloud Storage](/sensitive-data-protection/docs/automating-classification-of-data-uploaded-to-cloud-storage)\n: Implement an automated data quarantine and classification system using Sensitive Data Protection, Cloud Storage, and Cloud Run functions.\n\nCommunity contributions\n-----------------------\n\nThe following are owned and managed by community members, and not by the\nSensitive Data Protection team. For questions on these items, contact their\nrespective owners.\n\n[GitHub: Speech Redaction Framework](https://github.com/GoogleCloudPlatform/dataflow-speech-redaction)\n: Redact sensitive information from audio files in Cloud Storage.\n\n[GitHub: Speech Analysis Framework](https://github.com/GoogleCloudPlatform/dataflow-contact-center-speech-analysis)\n: Transcribe audio, create a data pipeline for analytics of transcribed audio\n files, and redact sensitive information from audio transcripts.\n\n[GitHub: Real-time anomaly detection using Google Cloud stream analytics and AI services](https://github.com/GoogleCloudPlatform/df-ml-anomaly-detection)\n: Walk through a real-time artificial intelligence (AI) pattern for detecting\n anomalies in log files.\n\nPricing\n-------\n\nWhen you inspect a Cloud Storage bucket, you incur\nSensitive Data Protection costs, according to the [storage inspection job pricing](/sensitive-data-protection/pricing#storage-pricing)."]]
