7 Best Practices for Data Loss Prevention

Most organizations generate and consume increasing amounts of data each year. Managing this data can be overwhelming, especially for organizations that haven't fully embraced digital transformation. As data grows, so does the risk of exposure to unauthorized parties through data breaches or leaks. Data breaches are among the most severe cybersecurity threats faced by organizations worldwide, and their frequency is expected to rise.

Data risk management is the process organizations use throughout the data lifecycle to enforce security and eliminate risk. This includes creation, acquisition, transformation, usage, and retirement of data. A key component of a successful data risk management program is Data Loss Prevention (DLP), which consists of tools and processes to ensure sensitive data isn't lost, misused, or accessed by unauthorized parties.

In this article, we’ll explore data loss prevention, its importance, and best practices for creating a DLP strategy and policy to protect your organization’s sensitive data from cybersecurity threats.

What is Data Loss Prevention?

Almost every organization creates, transmits, and stores sensitive data. Sensitive data is information that must be protected against unauthorized access to safeguard privacy or security. This can include intellectual property, databases, or spreadsheets containing Personally Identifiable Information (PII).

PII, such as names or birthdays, can be used by malicious actors for identity theft. PII may also include sensitive information like social security and driver’s license numbers. PII can belong to employees, customers, or stakeholders and is sometimes protected by law, such as the European Union’s General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA).

Data privacy laws protect consumers from having their data unintentionally leaked or lost due to malicious actors, insider threats, or unknowing employees. Data leaks or breaches can result in significant financial loss, reputational damage, and regulatory or legal consequences. The average cost of a data breach was $4.2 million in 2021, with costs going toward repairing reputational damage, loss of business, and non-compliance fines.

Even with regulatory standards in place, it often takes organizations a long time to identify a data breach—about 197 days on average. In 2021, more than 281 million people were affected by data breaches, surpassing the previous year by 17 percent. As more consumers are impacted by breaches, their expectations for data privacy increase. Organizations must prioritize DLP and transparency to remain relevant.

Most cybersecurity strategies focus on external threats like malware and phishing, but DLP strategies address internal threats such as disgruntled or negligent employees. Insider threats account for nearly 60 percent of all data breaches. A DLP strategy helps detect and prevent potential breaches by monitoring, detecting, and blocking sensitive data in use, in motion, and at rest.

Types of Data Loss Prevention

There are four main types of data loss prevention:

• ​Endpoint DLP (data in use): Data residing on devices such as desktop computers, laptops, USB storage devices, or virtual desktops.
• ​Storage DLP (data at rest): Unstructured data on servers or structured data in databases.
• ​Network DLP (data in motion): Data that transits or leaves the network, including emails.
• ​Cloud DLP: Data residing in the cloud or in personal email providers.

Your DLP strategy should address each type according to your organization’s needs and inform decisions about which DLP solutions to use.

DLP Solutions

A DLP strategy should integrate DLP tools, including software, with a holistic program to protect data from internal threats. This involves creating a DLP policy tailored to your business and selecting the best DLP solution to implement and maintain your program.

Most DLP solutions are designed to discover and analyze the content and context of your data to determine if it matches a defined pattern. When a match is found, the software generates a violation notification or alert for management review. Patterns may include social security numbers, credit card numbers, HIPAA terms, keywords, or other alphanumeric patterns.

DLP solutions often use fingerprinting algorithms to create unique identifiers for data and files. A discovery engine crawls your data, indexes it, and makes it accessible through an interface for quick searching and sensitivity assessment.

Most Common Data Loss Prevention Mistakes

Many organizations misunderstand DLP’s purpose, which is to restrict information flow both internally and externally. Implementing DLP can impact business operations, but the risks of not implementing it are often greater.

Some organizations focus too much on tuning DLP policies to eliminate false positives and not enough on actual blocking. With large amounts of sensitive information, you must decide which data to protect. Casting too broad a net increases false positives; too narrow, and you miss critical areas.

DLP is not designed to stop intentional leaks but can help you discover them. It mainly acts as a deterrent, signaling to staff that certain activities are monitored, which can reduce internal threats.

Creating the Best Data Loss Prevention Strategy

There is no one-size-fits-all approach to DLP. Your strategy should be tailored to your organization’s needs, but some best practices apply universally.

Pick the Right Team

Start by creating an internal DLP committee with senior leaders, business unit managers, legal, and infosec management. Clearly define roles and responsibilities, including data ownership and incident investigation duties.

Start with a Plan

Identify your most critical data (the “crown jewels”) and define metrics for monitoring. Decide what data to protect, where it resides, access conditions, incident response actions, archiving policies, and potential threats.

Build Out Your DLP Strategy

Use data discovery and classification technology to identify and control access to critical data. Implement access control lists (ACLs), encryption for data at rest and in transit, and avoid storing unnecessary data. Maintain a rigorous patch management strategy to keep systems up to date and secure.

Create Practical Policies and Procedures

Develop a DLP policy that balances security with usability. Test the policy through proof of concept exercises to ensure it meets compliance needs and identify deficiencies.

Educate End Users

Begin with an educational program to inform employees and stakeholders about the importance of DLP and what’s at stake. Many data loss incidents result from end-user mistakes, so awareness is key.

Shift the Culture

A successful DLP strategy requires a cultural shift, often needing executive support. Engage leadership to direct the program and provide solutions for any business process changes.

Monitor and Repeat

Regularly inform stakeholders about the DLP program’s status. Hold meetings for input and continuous improvement. Automate DLP processes where possible and choose solutions that support this.

Choose Tools to Help

Implementing a DLP platform can be expensive, so base investments on cost-benefit and risk assessments. Research vendors and consult industry peers. Choose software that fits your data management needs.

Best Practices for Data Loss Prevention (DLP)

• ​Classify your data: Categorize data by sensitivity and establish permissions and policies to restrict unauthorized access.
• ​Discover where sensitive data resides: Scan databases, file shares, email systems, and endpoints to locate confidential data. Monitor network traffic for suspicious activity.
• ​Establish user access controls: Permit access to sensitive data on a strict need-to-know basis. Use role-based access, encryption, and data masking.
• ​Set up DLP monitoring rules: Configure rules to detect potential breaches or policy violations in real-time.
• ​Standardize data security tools and initiatives: Use standardized DLP tools and protocols across your infrastructure.

Prevent Data Loss with the ZenGRC Platform

Organizations generate and consume increasing amounts of data, making manual management inefficient and risky. The ZenGRC platform enables strategic IT risk management by centralizing business activities and providing insights into IT and cyber risks. AI-driven relationships between assets, controls, and risks help alert you to changes in risk posture. Dashboards and reports provide contextual insights for informed decision-making.

Become more strategic with your IT risk management. Learn more about how the Reciprocity Product Suite can help your organization manage risks and compliance.