Enhancing Cloud Security and Protection with GCP Data Loss Prevention 

With businesses becoming increasingly reliant on data for extracting business insights, protecting and safeguarding this data becomes critical. The average monetary cost associated with a data breach in Canada is estimated to be around $4.5 million, and such events do irreparable harm to customer trust and brand reputation. 

The quantum of data that organizations possess, control, and leverage has grown monumentally over the last few years. The widespread adoption of Cloud services has opened new avenues for organizations to extract powerful insights from their data, at a previously unfathomable scale. However, cloud infrastructure is only as secure as users make it, especially when you account for the fact that 95% of cybersecurity breaches are due to human error. It is, therefore, essential that organizations make investments to fortify the storage, management, and protection of their data. 

When it comes to Cloud data security, organizations must address three key pillars to keep their data safe: Encryption and De-Identification, Anticipating Re-Identification Risks, and Access Control. 

Google offers Cloud Data Loss Prevention (Cloud DLP) as a fully managed service to help organizations discover, classify, and protect their most sensitive data. The service complements all Google Cloud Data services, including Cloud Storage and BigQuery, and its capabilities can be applied to virtually any data source, be it on Google Cloud, on-premise, or on any other cloud platform. 

With over 140 built-in infoTypes, Cloud DLP allows users to scan, discover, classify, and report on data, regardless of where it sits. It can be used for discovery and classification of both structured and unstructured data in real-time or at rest. For de-identification, it provides tools that can automatically mask, tokenize, bucket, and transform sensitive data to reduce compliance and security risks. The service also helps you better understand data privacy risks and identify statistical anomalies that can make your data vulnerable to re-identification. Cloud DLP also allows organizations to limit exposure of data to approved business users on a need-to-know basis, where they can only access it if they have a real business purpose that requires that data. 

In addition, Cloud DLP can be used in conjunction with Data Catalog to create an added layer of data governance. Together, the two services allow organizations to leverage metadata to identify which applications are the most vulnerable from a security perspective, and where you might have more sensitive/PII data that needs to be protected. 

This whitepaper deep-dives into the need for data loss prevention and security, so organizations can safeguard their data. It delves into the core capabilities of Cloud DLP and explains how the service works. We also share some best practices for using Cloud DLP and talk about how Adastra can offer a turn-key managed service for Cloud DLP, effectively taking responsibility for your organization’s data loss prevention capabilities. Adastra can give organizations the means to construct a formal process for defining, testing, and publishing enterprise-wide ‘filters’ (infoTypes) and provide services like API integration with applications and datasets, infoType lifecycle management, PII scans, and reporting, to address their long-term data protection requirements. 

As a proud Google Cloud Platform partner, we can help you get started with Google Cloud DLP and set your organization up for better security and protection of your data. Our experts can help scope your data, understand the intricacies and sensitivity levels of your data, and set up a working Cloud DLP model to safeguard your data assets. 

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