Data Loss Prevention (DLP): A Complete Guide

Data Loss Prevention Software

Data loss prevention (DLP) is critical for safeguarding sensitive enterprise data, making it essential for effective cybersecurity strategies. Here's your complete guide to building an effective DLP strategy!

Data is the new-age currency that drives the digital world. It brings forth profound insights, substantiates decision-making, and serves as the catalyst behind the evolution of innovation. Simply put, everything revolves around data.
Amidst this digital era, we are witnessing a dramatic shift in how assets are valued within an organization, moving from physical commodities to digital data. With the immense value that data holds comes the immense responsibility for organizations to protect it from imminent threats such as data breaches. This scenario catalyzes the need for data loss prevention. So, let's cut to the chase and delve deeper into what data loss prevention entails, and discuss whether every enterprise truly needs a data loss prevention solution.

What is DLP (Data Loss Prevention)?

Data loss prevention (DLP) is a security strategy designed for safeguarding enterprises' critical data from theft, loss, or access by unauthorized users. A good DLP system is a combination of tools for data discovery and classification, data transfer and access control, policy and incident management, and meticulous auditing and alerting.
Before jumping to the conclusion of whether your enterprise truly needs a DLP solution, it's important to understand why DLP is so essential. Having a DLP solution prevents the impact of data loss and theft. Let's explore how data loss happens.

What are the causes of data Loss?

Data exfiltration: Data exfiltration, often referred to as data extrusion or data exportation, is the unauthorized transfer of data from a network or endpoint over the internet. It can occur predominantly in two ways: by gaining physical access to the system or through the use of malicious programs.

Human error: Human error can be viewed as an outcome of negligence, an inherent characteristic of our flawed nature. A lack of awareness regarding data handling, lax adherence to security protocols, and failure to report incidents all contribute to this negligence. Additionally, the inability to comprehend the magnitude of these issues compounds the problem.

Insider threats: Insider threats are those that come from within, typically involving an employee with access to critical enterprise data and exposing it intentionally. The motivation behind every insider threat is often financial gain, causing reputational damage, or getting revenge.

While it's crucial to be knowledgeable about the causes of data loss, it's also essential to learn the importance of DLP to effectively gauge the potential impact of such data loss.

Why is DLP important for organizations?

A data breach is not a matter of if, but when. Given that a cyberattack happens once every 39 seconds, it's truly only a matter of time before your enterprise falls prey to this relentless cycle. Despite the ever-increasing surge in the amount of data produced, only 5% of company data is adequately protected. With each passing day, the definition of what is considered sensitive also broadens. In 2023, the expected average cost of a data breach per incident is estimated to be 5 million dollars.
Prevention is better than cure—an ancient adage that has only grown more relevant in our current age. No matter the strength of your recovery mechanisms, it is still essential to fortify your defense layer. In the realm of data management, a DLP system constitutes this defense layer. A DLP system in your enterprise will:

  • Safeguard critical data within your organization.
  • Classify enterprise data and restrict unauthorized access.
  • Ensure compliance with regulatory standards and government regulations.
  • Foster trust and enhance customer relationships.
  • Mitigate risks associated with insider threats.
  • Monitor and control sensitive data transfers.

What are the types of data loss prevention (DLP)?

There are three primary types of data loss prevention (DLP): Network DLP, Endpoint DLP, and Cloud DLP.

  1. Network DLP: This type of DLP offers comprehensive detection and protection capabilities across the enterprise network including cloud services. It covers email, web applications, and traditional data transfer channels such as FTP.
  2. Endpoint DLP: Endpoint DLP focuses on safeguarding network endpoints, including servers, desktops, laptops, and mobile devices.
  3. Cloud DLP: This form of DLP is dedicated to protecting data stored in cloud storage systems. It actively scans, monitors, and safeguards sensitive data movement within the cloud environment.

What are the examples of Data Loss Prevention (DLP)?

  • Restrict the transfer of intellectual properties through email or peripheral devices.

  • Restrict screen capture and clipboard use to prevent sensitive data leaks.

  • Control sensitive data transfer through private browsing or guest access.

Understanding the causes of data loss and acknowledging the potential significant costs if such an event occurs underscores the importance of a DLP system in any enterprise. It's becoming clear that a DLP system is no longer a choice, but a necessity to safeguard your enterprise from data loss, non-compliance, and insider threats.

How does DLP work?

DLP operates on three fundamental principles: detection, enforcement, and protection.

  • Detection
  • Enforcement
  • Protection

This stage involves identifying all the data within the enterprise network, regardless of its states (at rest, in use, or in motion). A comprehensive understanding of all data in various states is the cornerstone of keeping it secure. Once the data has been identified, the next step is to classify it based on the nature of the content and its context. This classification helps determine the appropriate security measures each data type demands.

After identifying and classifying sensitive data, the next step is to establish boundaries for data transfer across various mediums. These mediums include peripheral devices, cloud storage, email, web domains, and applications. While the most secure approach would be to block all sensitive data transfer attempts simply, such a stringent approach could impact productivity.
Since the movement of sensitive data is essential for the functioning of any enterprise, it's necessary to define clear boundaries and determine what can be transferred and through which medium. Most DLP systems achieve this by implementing policies.

Sensitive data transfer is permitted within defined boundaries but restricted when those boundaries are exceeded. Often, users are unaware that the data they are trying to transfer is considered sensitive. Educating users about the sensitivity of certain content can help prevent unintentional attempts to transfer sensitive data. Sometimes, certain data may be mistakenly classified as sensitive. In such cases, users have the option to raise the discrepancy and the controller should tweak the policy accordingly.

What does Data Loss Prevention do?

Simply put, DLP software scans all the data present in your enterprise network, classifies data based on what is sensitive to your enterprise, blocks unauthorized attempts to transfer sensitive data, addresses false positives, and provides continuous auditing and reporting of events.

What are the use cases of data loss prevention (DLP)?

In this digital era, every enterprise is embarking on a digital transformation journey, whether they are a new digital entity transitioning from traditional to digital systems or an established digital being implementing measures to safeguard critical data. DLP is crucial for both.

Here are a few use cases of DLP to help you understand better.

  1. Previously, credit cards and other bank details were highly valued in the black market, but they have now been surpassed by a new obsession: medical records. This is because a comprehensive medical record could encompass nearly every piece of documentation a person might own. The rise in medical-related crimes, needless to say, further emphasizes the magnitude of this issue. In the healthcare sector, data loss prevention software is not a choice but a must.
    DLP software could safeguard the sanctity of medical data, forbid unauthorized medical data transfers, and meticulously log all movement of medical data within the network.
  2. Every country has its own data compliance standards, which ensure that organizations abide by laws and regulations related to data handling. For instance, the General Data Protection Regulation (GDPR) in European nations is a measure designed to protect personal data rights. Similarly, the California Consumer Privacy Act (CCPA) is in effect in the US while the Personal Information Protection and Electronic Documents Act (PIPEDA) serves the same purpose in Canada. Non-compliance with these standards can result in hefty fines. DLP software can help organizations stay compliant with these compliance standards.
  3. Human resource management is an integral part of an organization. It involves the collection and storage of employees' personally identifiable information (PII), by which an individual can be identified. PII is one of the most valuable types of data, and many regulations advocate for its protection as a mandatory requirement. In this use case, DLP software could be used to identify PII data and prevent unauthorized access or transfer.

What are the benefits of DLP (Data Loss Prevention)?

A data loss prevention solution offers comprehensive visibility into your data, enabling precise control over its transfer while automatically detecting and flagging potential security risks. In essence, such a system serves three primary functions: preventing data loss, ensuring regulatory compliance, and safeguarding your organization's reputation.

Data loss prevention (DLP) best practices

Define the data rule for you
There are a gazillion data classification standards based on another gazillion parameters. If you consider all available data classification standards, every other file will be marked as sensitive, but doing so will affect the collective productivity of your enterprise. What is sensitive to your country, industry, or organization might not be sensitive to others. Therefore, being specific is the way to go. It is recommended to define data rules specific to your country and enterprise-specific demands.

Ensure to include trusted applications and domains in the policy
Every enterprise has a set of indispensable applications, domains, devices, printers, and more for smooth functioning. Remember to include these indispensables while deploying a data loss prevention policy to achieve data security without compromising productivity.

Keep your data classification database updated
The emergence of newer data classification rules as well as regular enhancements of existing data rules is fairly common as security standards continue to evolve. it is Because these regulations are always under improvement, there's a high chance of missing one of the latest updates. But leveraging these essential updates is vital to ensure the security policies deployed are the latest and most secure. Despite your network constraints, it is recommended that your server is connected to the internet with a proper proxy setup.

Label files downloaded via enterprise domains as sensitive
If a file is downloaded via enterprise domains, there’s a high chance it contains sensitive data. To be safe, always mark files downloaded via the enterprise domains as sensitive. This is a proactive approach towards identifying and securing enterprise data.

Why Endpoint DLP Plus?

ManageEngine Endpoint DLP Plus provides a comprehensive catalog of data loss prevention features specifically designed to safeguard your enterprise's critical data from loss and insider threats. With Endpoint DLP Plus, you can define what data is sensitive to your organization and protect it using extensive data discovery and a robust data classification protocol. The platform simplifies data classification by offering both pre-defined and customizable templates. Additionally, auditing, tracking, and data rules are included to ease the burden of meeting compliance with regulatory standards.