The Ultimate Guide to Data Loss Prevention in the Cloud

Most businesses rely on cloud services, including SaaS applications like email and collaboration software and file storage solutions. However, these services are not immune to cyber threats and data loss.

A comprehensive backup and recovery solution must protect all versions of files and ensure data integrity. That means deploying an automatic DLP process.

How DLP Works

To secure data loss prevention for the cloud, IT needs visibility into where that information resides and how it moves. The complexities of the cloud make this type of visibility difficult. Fortunately, DLP can solve this challenge.

DLP can protect sensitive data in motion and at rest by monitoring for risky activity. It can also encrypt data, enforce access controls, and monitor compliance with HIPAA, PCI DSS, and GDPR. DLP solutions can also reduce the risk of data breaches by detecting negligent or malicious employee behavior.

Many data loss prevention tools use pattern-matching to identify and block sensitive information, like credit card numbers or social security numbers. However, this method can bombard security teams with too many false positives and may only identify some risky traffic. A better solution is to implement exact data match (EDM), which “fingerprints” sensitive data and watches for attempts to move the fingerprinted information.

DLP can help organizations reduce the impact of expensive data breaches that damage company reputations. A breach exposes end users’ personal information and can result in lost business, legal action, and fines from regulators. While external threats are a significant concern, the Verizon 2023 Data Breach Investigations Report shows that over half of all data breaches involve human elements, such as negligence or privileged misuse.

Best Practices for DLP Implementation

The most critical first step is identifying the data you need to protect. This involves determining which data, if lost, would cause the most harm to stakeholders and should be covered in line with regulations like GDPR and HIPAA. It also involves understanding the sensitive information your business processes, such as PII, payment card data, and confidential documents.

Next, you must build and enforce policies to prevent the loss of sensitive information. This includes encrypting data, limiting access to sensitive files, and protecting data in transit. It’s also essential to set up alerting mechanisms to detect anomalous activity and notify appropriate individuals when a potential data loss occurs.

Finally, you must train employees and enforce the Principle of Least Privilege. This means granting access only to those who need it and regularly revoking access that’s no longer necessary. Creating incident response protocols and testing these regularly using real-time drills is also a good idea.

Most DLP solutions work by comparing sensitive information against a database of rules. These rules are ranked by priority, and the program executes them in that order. Some DLP programs also utilize machine learning to improve regulations and generate new ones. Additionally, some DLP tools can be remediated at a granular level in individual apps, which is essential for eliminating user frustration and preventing shadow IT.

DLP Deployment Strategies

Many of today’s most common data breaches involve human factors, such as privilege misuse and social engineering. Consequently, the Verizon 2023 Data Breach Investigations Report found that 75% of all violations included losing sensitive information due to insiders. This underscores the importance of DLP.

DLP solutions monitor and control critical data in software-as-a-service (SaaS) applications and infrastructure-as-a-service resources. They detect sensitive information in cloud storage and encrypt it to prevent it from being leaked or removed. They also support a variety of security controls to comply with compliance and privacy regulations.

Traditionally, DLP solutions rely on pattern-matching to identify and protect sensitive information such as credit card numbers or Social Security Numbers. However, this imprecise approach can bombard security teams with false positives, causing unnecessary delays in protecting the organization’s data. More advanced solutions use exact data match (EDM), a process that fingerprints sensitive information and watches for attempts to move it, thus eliminating the risk of false positives.

In addition to deploying DLP solutions, educating employees about protecting sensitive information is essential. This includes establishing a list of accepted protocols, programs, and data-handling procedures. DLP programs can also be augmented with CASBs that combine context (device, network, and user) and content (data classification) to define more granular security controls.

DLP Tools

DLP software and tools monitor data streams on endpoints, corporate networks, and cloud environments to prevent unauthorized use of sensitive information, insecure storage, and unencrypted transfers. They also help meet auditing and compliance requirements and identify areas of weakness and anomalies for forensics and incident response.

Some DLP solutions offer automation capabilities that enable enterprises to implement policies that instantly notify users of sensitive data or automatically block specific actions such as file downloads, print operations, email forwarding, and other file-sharing activities. This eliminates the need to review security alerts manually and reduces risk until admins and security staff can act.

Another type of DLP solution is a data discovery tool that scans an organization’s systems and clouds to identify and catalog sensitive information. These tools can then apply various protection measures to these assets, including zero trust encryption, to ensure unauthorized parties cannot view cloud content in plain text.