Cloud Data Loss Prevention

Use cases of Cloud Data Loss Prevention

De-identifying sensitive data 

With Cloud DLP, you can automatically understand and manage your data risk across your organisation. You can manage and reduce your data risk, stay compliant, and make more informed decisions as you have continuous visibility of your data. 

You may easily configure data profiling in the Cloud Console without managing any jobs or overhead, letting you to focus on the outcomes and your business.

Redacting sensitive data from images 

Using cloud data loss prevention, private text can be removed from images. Cloud DLP scans an image for text using  infoType detectors and Cloud Vision, finds sensitive data inside the text, and then returns an image with any matching sensitive data covered by an opaque rectangle.

Take a look at the following "before" and "after" images as an example. A typical image file created from a scan of a paper document is the original picture. In this illustration, Cloud DLP has been set up to use a variety of coloured rectangles, depending on the content, to redact US Social Security numbers, email addresses, and phone numbers.

Inspecting storage and databases for sensitive data

The key to properly managing sensitive data stored in a storage repository is storage classification, which entails figuring out where your sensitive data is kept in the repository, what kind of sensitive data it is, and how it is used. With this knowledge, you can correctly set up access control and sharing permissions as a part of a plan for continuous monitoring

Sensitive data stored in a Cloud Storage location, Datastore kind, or BigQuery  table can be detected and classified using Cloud Data Loss Prevention. Cloud DLP supports scanning of binary, text, image, Microsoft Word, Microsoft Excel, Microsoft Powerpoint, PDF, and Apache Avro files while scanning files in Cloud Storage locations. Unrecognised file types are examined as binary files. See Supported file types for further information on the Supported file types that are.

 Protect sensitive data as you migrate to the cloud

As you migrate more workloads to the cloud, unblock them. You may inspect and classify your sensitive data in both structured and unstructured workloads with cloud DLP.

By obfuscating the raw, sensitive identifiers, de-identification techniques like tokenization (pseudonymization) enable you to preserve the utility of your data for joining or analytics while reducing the handling risk.

Cloud DLP Safety Tips

Here are some steps your organisation should take to ensure that data loss prevention is emphasised:

• Prioritize Data 

          You need to figure out which data is most vulnerable to theft and is most likely to be the target of attackers.

• Classify the data

Connecting a category to the user or programming that generated the data. Data that is commonly known to be sensitive includes credit card information of customers, vendors, and others as well as social security numbers. There are also pre-configured rules for the payment card industry (PCI), personally identifiable information (PII), and related subjects.

• Understand when data is at risk

When files in the cloud have broad sharing permissions like public, external, or internal across all tenants, they are often at risk. Furthermore, highly targeted and privileged users owning the sensitive files may also be at risk.

• Monitor data in motion

To keep track of what's happening to their sensitive data and to determine the scope of any issues that their cloud-based DLP strategy needs to address, organisations must monitor data in motion.

• Practice exact data matching

Exact data matching enables you to create a custom dictionary item or the other custom identifiers for your company or industry that are unique, such as account numbers for financial services, local forms of identification, or medical record numbers.

Now, let us discuss some FAQs based on the above discussion.

Frequently Asked Questions 

What is the data loss prevention in the cloud?

Sensitive or critical information held by an organisation is safeguarded from cyberattacks, insider threats, and unintentional disclosure with the aid of cloud data loss prevention (DLP). Sensitive data in SaaS and IaaS applications is visible and protected by cloud DLP solutions.

What are the three types of data loss prevention?

There are three main types of data loss prevention software that includes network DLP, endpoint DLP and Cloud DLP.

To prevent data loss what methods are used?

For laptops that hold confidential data, full-disk encryption or the ability to remotely wipe a computer are critical to protecting business from a data breach. Additionally, having a reliable backup in place will guarantee that you don't lose that critical data.

What causes data loss the most commonly?

The majority of business-related data loss is believed to have been caused most often by human error. Additional factors include software corruption, computer viruses, hardware degradation, natural disasters, and power failures.

What are the reasons why cloud computing experiences permanent data loss?

Due to malicious attacks or accidental or deliberate deletion by a cloud service provider, data can be lost permanently. When data is encrypted and the encryption key is lost, the data is also lost.

Conclusion

In this article, we have extensively discussed Cloud Data Loss Prevention, its advantages and benefits. Further we have also discussed the use cases and some FAQs. We hope that this blog has helped you enhance your knowledge regarding Cloud Server, and if you would like to learn more, check out our articles on 
 

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