What Is Cloud DLP (Data Loss Prevention)?

Why Cloud DLP Is Essential for Modern Businesses

In the era when sensitive information was printed on paper, loss prevention could be as simple as a locked file cabinet. Now, data races between data centers, cloud providers, and endpoint devices, potentially subject to myriad vulnerabilities along the way. To protect it against unauthorized access, you need to implement a comprehensive data loss prevention (DLP) strategy.

Your DLP strategy should bring your business and IT leaders together to identify what constitutes “sensitive data” for your organization, agree on how this data should be used, and delineate what a violation looks like. These information security guidelines, including data classification, data privacy and compliance information, and remediation procedures, can then be translated into DLP policy.

Various compliance standards (e.g., GDPR, HIPAA, PCI DSS) might require your organization to deploy DLP to avoid fines or restrictions to your operations, but data breaches can also expose end users' personal data, putting your organization at risk of losing customers, incurring brand damage, or facing legal consequences. With a well-defined DLP policy bolstered by well-managed supporting technology, you can significantly reduce these risks.

Understanding the Risks of Data Loss in the Cloud Era

As organizations accelerate their cloud adoption and fine-tune their hybrid work models, the attack surface has expanded dramatically. Today's threat landscape presents unique challenges that traditional security approaches struggle to address, requiring organizations to understand and mitigate the following critical risks:

• Shadow IT and unsanctioned cloud applications: Employees increasingly use unauthorized cloud services to share and store sensitive data, creating visibility gaps where IT teams cannot monitor or protect critical information flowing outside approved channels.
• Sophisticated ransomware and supply chain attacks: Modern threat actors target cloud infrastructure and third-party integrations to encrypt or exfiltrate data at scale, exploiting trust relationships and API connections to maximize damage across interconnected systems.
• Remote workforce vulnerabilities: With distributed teams accessing corporate data from personal devices and unsecured networks, organizations face increased exposure to data leakage through unmanaged endpoints, public Wi-Fi, and compromised home networks.
• Cloud misconfigurations and API exposures: Complex cloud environments often suffer from misconfigured storage buckets, excessive permissions, and exposed APIs that inadvertently make sensitive data accessible to unauthorized parties or the public internet.

Top Benefits of Using Cloud-Based Data Loss Prevention (DLP)

Cloud-based DLP offers several advantages to any organization, providing:

• Easy scalability to meet the needs of growing data volumes and changing information ecosystems
• Lower infrastructure costs due to eliminating on-premises hardware and related refresh/maintenance expense
• Protection for users and branches anywhere without the need to backhaul to your data center
• Faster deployment and configuration than on-premises DLP, with no boxes to manage
• Automatic updates from the cloud, providing the latest intel and new features without downtime

How Cloud DLP Works: Key Techniques and Strategies

In the simplest terms, DLP technology, including cloud-based DLP, works by identifying sensitive data in need of protection, and then protecting it. A DLP solution may be designed to identify data in use, data in motion, or data at rest (or any combination) and determine whether it is sensitive. To do this, DLP agents may use many different techniques, such as:

• Rule-based matching or "regular expressions": This technique identifies sensitive data based on prewritten rules (e.g., 16-digit numbers are often credit card numbers). Because of a high false positive rate, rule-based matching is often only a first pass before deeper inspection.
• Exact data matching (database fingerprinting): This technique identifies data that exactly matches other sensitive data already fingerprinted, usually from a provided database.
• Exact file matching: This technique works essentially like exact data matching, except it identifies matching file hashes without analyzing the file's contents.
• Partial document matching: This technique pinpoints sensitive data by matching it to established patterns or templates (e.g., the format of a standard patient form in an urgent care facility).
• Machine learning, statistical analysis, etc.: This family of techniques relies on feeding a learning model a large volume of data in order to "train" it to recognize when a given data string is likely to be sensitive. This is particularly useful for identifying unstructured data.
• Custom rules: Many organizations have unique types of data to identify and protect, and most modern DLP solutions allow them to build their own rules to run alongside the others.

Once the sensitive data is identified, it's up to your DLP policy to determine how the data is protected. In turn, how you protect it has a lot to do with why you want to protect it.

Cloud DLP vs. On-Premises DLP vs. Traditional DLP

Organizations evaluating DLP solutions must understand the fundamental differences between deployment models to make informed decisions. Each approach offers distinct advantages and limitations that directly impact security effectiveness, operational efficiency, and total cost of ownership.

Main Use Cases for Cloud DLP

As we've already covered, securing sensitive data protects your organization against other forms of loss—of customers, of revenue, of reputation—and helps you comply with industry and legal regulations. Protecting this data naturally requires being able to identify what and where it is, which constitutes another key use case: data visibility.

So, in short, the main use cases for a DLP solution are:

• Protecting sensitive data in motion and at rest: DLP protects data as it moves among or is stored within multiple endpoints, networks, and clouds by providing encryption, enforcing access controls, and monitoring for suspicious activities.
• Staying compliant with regulations: DLP policies and technologies help you enforce access controls, monitor usage, and conduct audits to ensure you handle sensitive data in alignment with regulations like GDPR, HIPAA, and PCI DSS.
• Getting visibility into your data: DLP provides data visibility—insights into where sensitive information resides and moves, who has access, and how it is used—to help you identify vulnerabilities, detect risky activity, and ultimately remediate and stop data breaches.
• Securing remote work environments and personal devices: With the rise of remote workforces and bring your own device (BYOD) policies, DLP helps enforce security policies across a diverse range of devices and locations, reducing the risk of data leakage outside traditional network boundaries.

5 Types of Cloud DLP Solutions

Because no single technology can cover every use case or account for every way data can be lost, today’s effective data protection offerings integrate multiple functions. Let’s look at some of the most common and crucial cloud DLP technologies.

• Cloud access security brokers (CASBs) monitor and control user activity and data transfers between endpoints and cloud apps, enforcing security policies to prevent unauthorized access, data leaks, and compliance violations. CASB offers visibility into user behavior, app usage, and data storage in cloud environments.
• DLP software protects sensitive data against data leakage across endpoints, email, cloud services, and other channels. By monitoring data and enforcing policies in real time, DLP software identifies and prevents potential breaches.
• User and entity behavior analytics (UEBA) monitor, analyze, and correlate user behavior, access patterns, system events, and more to detect anomalies and potential threats, such as malicious insider threats, compromised accounts, and lateral movement.
• SaaS security posture management (SSPM) helps organizations assess and manage security configurations, permissions, and vulnerabilities across different SaaS apps to address security gaps and mitigate risks associated with data exposure and unauthorized access.
• Browser isolation executes web content in a secure environment, preventing potentially malicious web content (e.g., drive-by downloads, malware, phishing) from directly accessing or affecting the user's endpoint, network, or sensitive data.

Data Visibility: The Foundation of Effective Cloud DLP

DLP can’t prevent data loss if it’s blind to traffic. This is crucial as organizations continue to move more and more data in the cloud, where three key challenges leave traditional network-based DLP unable to see the traffic it’s supposed to inspect:

• Remote users: With network DLP, the levels of visibility and protection depend on where users are. They can easily bypass inspection when off-network, connecting directly to cloud apps. Effective DLP and security policies must follow users wherever they connect, and on whatever devices they may be using.
• Encryption: The incredible growth of TLS/SSL-encrypted traffic has created a significant blind spot for network-based DLP incapable of decrypting it for inspection.
• Performance limitations: Appliance-based DLP solutions have finite resources that constrain them from scaling effectively to inspect the constantly growing amount of internet traffic inline.

Why Cloud DLP Is Critical for the Modern Cloud and Mobile-First Enterprise

To address the data protection challenges that accompany digital transformation and overcome the weaknesses of traditional enterprise DLP, you need a new mindset and new technology. Reconfiguring a traditional hardware stack for the cloud isn’t enough—it's inefficient and lacks the protection and services of a cloud-built DLP solution, including:

• Identical protection for all users on- or off-network, ensuring comprehensive data protection for all users, wherever they are—at HQ, a branch, an airport, or a home office.
• Native inspection of TLS/SSL-encrypted traffic, giving the organization crucial visibility into the traffic where more than 85% of today’s attacks hide.
• Elastic scalability for inline inspection, preventing data loss by inspecting all traffic as it comes and quarantining.

Cloud DLP Best Practices

The perfect DLP strategy depends on your organization’s data and its needs, so the best practices will vary—but that’s a subject for an entire article. Here, we’ll look at some broader DLP best practices that apply in any situation:

• Start in monitor-only mode when you first deploy to get a sense of the data flow across your organization to inform you on the best policies.
• Keep employees in the loop with user notifications so that policies aren't executed without their knowledge, as this can disrupt workflows and frustrate them.
• Ensure your users can submit feedback on notifications (to justify their actions or flag broken policies), which you can use to refine your policies.
• Leverage advanced classification measures like EDM to reduce false positives.

Get Started with Zscaler Cloud Data Loss Prevention

100% cloud-delivered Zscaler Data Loss Prevention, part of Zscaler Data Security. Zscaler DLP empowers you to close your data protection gaps no matter where your users or applications are—while simultaneously reducing IT cost and complexity.

Zscaler DLP provides:

• Identical protection for users and data anywhere
• Protection across internet, endpoint, email, SaaS, private apps, and cloud posture
• Scalable TLS/SSL inspection from the world’s largest inline security cloud
• Streamlined workflows and operations with innovative ML-powered data discovery

Ready to see how Zscaler DLP can safeguard your organization? Request a demo today!