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What Is Data Loss Prevention? Complete Guide [2022]

Shiv Sujir - September 15, 2022

Data Loss Prevention (DLP) prevents users on a corporate network from sending sensitive data outside the network. DLP solutions help network administrators control data flow on a network and establish strict controls over private, sensitive, or otherwise valuable data. 

DLP typically works by allowing administrators to classify data via business rules. Any data classified as sensitive is protected by preventing users from accidentally or maliciously sharing or exposing it. DLP can monitor and control activity on user endpoints and also filter data streams from corporate networks to protect data in motion.

A typical use case is email security—a DLP solution can monitor emails sent by employees, and if an employee attempts to send or forward an email with a sensitive attachment, the email will be blocked before it leaves the corporate email server.

DLP can help organizations combat internal threats and meet data privacy laws. Many countries have data privacy regulations that require companies to establish strict protection and access controls over certain types of data, and DLP can establish some of the required controls.

Causes of Data Loss

There are two primary types of data loss:

  • Accidental data loss is mainly due to human error, such as sharing files with the wrong person or accidentally editing the wrong file. It can also be caused by factors outside the organization’s control, such as technical malfunctions or misconfigurations. Accidental data loss has similar consequences to malicious data loss and can expose the company to legal liability, regulatory fines, and loss of customer trust.
  • Malicious data loss results from internal or external malicious acts. It occurs when an employee, contractor, or customer feels they were wronged by the company or has a financial motivation, causing them to steal company data. It can also be caused by third-party attackers using social engineering, misconfigurations, or third-party integrations, to compromise an organization’s systems and exfiltrate data. Attacks may be targeted directly at the company or at its trusted partners or vendors.

How Does Data Loss Prevention Work?

DLP software monitors, detects, and blocks sensitive data from leaking out of an organization. This means monitoring both incoming and outgoing data flows on the corporate network.

Most DLP software products focus on blocking specific, suspicious actions. For example, if an employee attempts to forward a work email, upload a company file to a private cloud storage service, or save files to a USB disk, the action is blocked.

In addition, DLP can detect suspicious activity in incoming emails, looking for suspicious attachments and hyperlinks that might indicate a phishing attack. DLP allows administrators to flag suspicious emails, either blocking them entirely or saving them in quarantine for manual examination.

In the past, DLP detection and blocking were based on static rules set by the security team, but this was labor-intensive and easily bypassed. Modern DLP software uses machine learning algorithms to identify a baseline of normal behavior and identify emails or data flows that are “unusual” and warrant further investigation.

DLP Use Cases

Compliance with Industry and Government Regulations

Many organizations have legal obligations to protect sensitive data or are subject to binding industry standards. These include:

  • Health Insurance Portability and Accountability Act (HIPAA) covers US healthcare organizations and their partners.
  • General Data Protection Regulation (GDPR) covers any organization that does business with European Union citizens.
  • Payment Card Information Data Security Standard (PCI DSS) covers organizations that process or store credit cardholder data.
  • California Consumer Privacy Act (CCPA) covers any organization that does business with California citizens.

In these and similar compliance standards, sensitive data must be stored in a secure location and isolated from unauthorized users. Businesses must implement DLP policies and tools to prove they have taken sufficient measures to prevent accidental or malicious exposure of sensitive data stores.

Intellectual Property (IP) Protection

A company’s IP can include data or knowledge about an organization’s business structure and operations, products, customers, or partners. Common examples include business plans, proprietary source codes, patents, customer lists, and internal process documents.

IP is a valuable target for hackers because they can obtain monetary gain by selling or disclosing it. Many ransomware attackers today will not only demand a ransom to unlock a victim’s data but also extort the organization and threaten to expose its data in exchange for a ransom.

DLP software can help protect intellectual property from external attacks and breaches, as well as prevent accidental exposure of IP. Unintentional sharing of sensitive data or information via insecure media or public cloud accounts can do just as much damage as malicious activity.

Data Visibility

An enterprise DLP solution allows organizations to view and track data across endpoints, networks, and clouds. This allows administrators and security teams to understand how individual users in an organization interact with data. These valuable insights can be used to plan more effective data policies and inform security awareness training.

Types of DLP Solutions and Tools

Network DLP

Network data loss prevention (DLP) software can monitor, detect, and stop sensitive data before it leaves the network. Many compliance standards specifically require that organizations demonstrate they have measures in place to prevent the exfiltration of sensitive information through the network.

Network DLP can protect intellectual property (IP) and increase employee security awareness. It is important not only to detect and prevent accidental data loss but also to prevent malicious insiders from intentionally stealing data and transferring it through corporate networks.

Endpoint DLP

Endpoint DLP monitors all endpoints, including servers, computers, laptops, mobile phones, and other devices that use, move, or store data. Endpoint DLP solutions protect data in use, in transit, and at rest, by installing agents on any endpoint device that accesses or stores sensitive corporate data. These agents can:

  • Apply predefined policies to data accessed by authorized users and applications, blocking activities that violate those policies.
  • Use encryption to protect data sent to portable devices, ensuring that only the intended users can access it.
  • Scan sensitive data on the endpoint and respond to mishandling of sensitive data.

Cloud DLP

Cloud DLP is becoming increasingly important for data security as organizations around the world move to remote operations. Cloud DLP solutions can be used both by remote employees and office locations. Cloud DLP can encrypt data stored in cloud systems and ensure it is transmitted only to authorized users or applications. Some cloud DLP products anonymize or obfuscate sensitive data to mitigate the impact of a data breach.

Cloud DLP extends enterprise data security controls to the cloud, enabling consistent data security and management across on-premise data centers, software-as-a-service (SaaS) applications, and infrastructure-as-a-service (IaaS) resources.

Key Features of Data Loss Prevention Software

Content Analysis

Content analytics is the ability of a solution to analyze sensitive data, classify it, and group similar data together, to protect it via the most appropriate security measures.

Most DLP solutions provide a list of content analysis features, including:

  • File cracking—a way to extract and analyze content even if it is embedded within another file. For example, even if the content is archived in a ZIP file or files are embedded in an Office document, the DLP solution should be able to analyze them.
  • Encryption—DLP should be able to identify encrypted files and integrate with key management systems to enable decryption and analysis of data on the fly. Even if data was not encrypted by the organization, the solution should be able to identify it and make reasonable assumptions about its content.

Administration Console

A DLP solution should have a robust admin console that allows teams to manage the solution. It should provide a dashboard useful for both technical and non-technical users (such as executives or legal staff). A DLP console should include:

  • Hierarchical management of data policies within an organization
  • Integration with user directory services such as Active Directory or LDAP
  • Role-based permission management
  • Clear visibility over data flows across the organization
  • Alerting and notifications that allow security teams to respond to suspicious activity

Policy Management

The policy management function allows teams to create, apply, and modify security policies based on the company’s requirements. A DLP solution should allow teams to construct policies by defining:

  • Which data to protect
  • Which data sources to protect
  • Which channels to monitor and protect
  • Which devices or endpoints to protect
  • What actions to take in case of policy violations
  • Which users should be able to view or edit the policy

Real-Time Analytics

DLP solutions should provide instant alerts or notifications based on real-time analytics of protected data. Real-time alerts notify security professionals of incidents, allowing them to take action when needed.

Another aspect of real-time analytics is that it enables visibility over data flows across the organization. A DLP solution should have reporting capabilities, allowing administrators to monitor data security and solution performance for their own use or to present it to stakeholders in the organization. DLP solutions should also support creating compliance reports in the format required by auditors. 

DLP Best Practices and Strategies

Data loss prevention best practices relate to technologies, processes, expertise, and awareness training. Here are some tips for creating an effective DLP plan:

Use a Centralized DLP System

Organizations often use inconsistent DLP tools and practices implemented by different teams. This lack of coordination results in visibility gaps and security weaknesses, while teams often ignore the DLP programs that only one department handles.

Assess the Organization’s Resources

Experienced DLP personnel are essential to creating and enforcing a DLP strategy. Organizations may have to employ internal data protection experts to comply with certain regulations. For instance, companies subject to the GDPR must have a staff member like a DPO (data protection officer) to conduct audits, monitor performance, and train employees.

Take Inventory and Evaluate Company Data

One of the first steps when building a DLP strategy is to evaluate the types of data stored or processed by the organization, including a business value assessment. The organization must identify sensitive data and keep track of where it’s stored. Some DLP solutions can scan and identify assets, enabling analysis and listing of the results.

Next, it is important to assess the risk posed by the data if leaked. For instance, losing data can cost the organization, especially if it contains business-critical information. Different data types carry different risks.

Use a Phased Implementation Approach

It is best to implement DLP as a long-term project broken into distinct stages, starting with high-priority data types. An organization can implement DLP tools piecemeal rather than in one burst. Inventory and risk analysis help prioritize the data.

Establish a Data Classification System

Before implementing a DLP policy, it is important to have a framework to classify structured and unstructured data. Data security classes could include public and confidential data divided into internal, financial, and regulated data. DLP solutions scan data with a customizable taxonomy to identify key data categories. This process requires human involvement, even if the software speeds up the classification tasks. Content owners can evaluate content types unidentified by automated tools.

Create Data Management Policies

Organizations should create or update their policies for handling various data categories. Government regulations often specify DLP policy requirements for sensitive data management. A DLP solution typically applies predetermined policies and rules based on regulations like HIPAA and the GDPR.

DLP teams can customize policies to an organization’s needs and enforce them with software that monitors and blocks outbound channels. For example, employees trying to send emails with sensitive information may receive suggestions to encrypt the message, or the tool could block the emails directly. 

Train Employees

Staff awareness of security policies is essential to enforce DLP. Organizations should periodically conduct training sessions and send emails to keep employees up to date with data security requirements. It can help to apply penalties for noncompliance and data security breaches.

Data Loss Prevention with Pathlock

Pathlock is the leader in Application Security and Controls Automation for business-critical applications. Pathlock streamlines and automates critical processes like fine-grained provisioning, separation of duties, and detailed user access reviews to enhance application security and compliance. Depending on your DLP goals, Pathlock offers a suite of solutions that enable you to restrict or allow access to data based on contextual attributes.

Attribute Based Access Controls: Grants access to users through the use of policies that are automatically enforced using context-aware attributes (e.g., location, time range, days, security clearance level, IP address, max dollar amount allowed to be entered, even require a manager review, etc.). ABAC functions as a preventative control at the business process, transaction, and master data level.

Dynamic Data Masking: Apply full or partial data masking on any desired field, using a centrally managed rule for easy implementation. Users can dynamically deploy masking based on the context of access, like remote, mobile, and time of day.

User Activity Monitoring: Pathlock captures granular transaction details like what data was accessed, by whom, from where/what device, and why. Having this level of visibility enables you to effectively monitor the myriad of risks that threaten your sensitive data.

Interested to learn more about Pathlock’s Data Loss Prevention capabilities? Request a demo today to see the solution in action!

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