Data Loss Prevention (DLP): Working, Importance, and Types Explained

Importance of Data Loss Prevention (DLP)

Data Loss Prevention (DLP) is a technology that is used to detect and prevent the leakage of confidential and sensitive data out of the enterprise. It helps in avoiding the loss of intellectual property, private data, or any other information that could possibly be misused by unauthorized people. All these processes are done without affecting the overall workflow of the organization. Read the blog to find out more about Data Loss Prevention (DLP) working, importance, and types.

Table of Contents

Causes of Data Leaks? 

There can be several reasons behind the leakage of confidential data, such as: 

  • Employees leaving an organization and taking away important files with them
  • Employees sharing passwords with others
  • Unauthorized transfer of files through pen drives and external hard disks
  • Intentional or unintentional emailing of important documents to external parties
  • Careless disposal of files or printing them on the wrong printers

Types of Data Leaks

End Point DLP consists of 3 major types of Data Leaks 

  1. At rest – stored data, portable storage
  2. In use – cut/paste, application activity, data classification 
  3. In Motion – network traffic when remote, print/ fax/ internal network traffic 

Different Data Leak Channels : 

  • Plug and Play Devices
  • Wireless Media 
  • Email 
  • WebMail 
  • Instant Messaging
  • Blogs
  • Social Media 
  • Web Pages 
  • Hard Copy 
  • Encryption Technologies

Insider threats are still one of the major causes of data leaks across organizations. DLP tools and software enable companies to scan and control endpoint activities. They also help filter data streams on the corporate network and protect data in motion. 

Types of DLP Solutions? 

Email DLP:

Protect your business from phishing and social engineering by detecting incoming and outgoing messages based on preset criteria and policies. 

Endpoint DLP:

By installing software on endpoints such as PCs, laptops, mobile devices, servers, etc., sensitive data is monitored and protected using endpoint DLP solutions even when the devices are offline or connected to the network. 

Network DLP:

Devices connected to the given network will be enforced with policies. The incoming and outgoing data is monitored, blocked, protected, and prevented from traveling from any device connected to the given network.  

Cloud DLP:

Allows much stronger DLP visibility and protection compared to other solutions and requires no hardware and software for setting up.  

How does DLP work? 

The two main technical approaches to DLP solutions include 

1. Context Analysis for analyzing data:

looks at metadata and other properties of the document, such as header, size, and format

2. Content Awareness based on string matches:

Involves reading and analyzing a document’s content to identify if it includes sensitive/confidential information

In the first stage, the DLP solution examines the context of a document to see if it can be classified. It explores the document using content awareness only if the context is found insufficient at stage 1.

While processing the content, multiple content analysis techniques are used to surface policy violations including: 

  1. Rule-Based/ Regular Expressions: This is the most common analysis technique used in DLP. in this technique, the sensitive content is analyzed for specific rules or regular expressions such as 16-digit credit card numbers, 9-digit security numbers, etc. This approach is highly effective as an initial filter and is proven easy to configure and process. Usually, this method comes with additional techniques. 
  1. Structured Data Fingerprinting: Also known as Exact Data Matching. This method involves creating a Fingerprint of the data and searching for the exact matches in the database dump or a live database. 
  1. Exact File Matching: The hashtag algorithm is used to create an entire file. While analyzing the content, the files matching the hash are searched. This highly accurate technique cannot be used on files with multiple versions. 
  2. Partial Document Matching: Used to identify files with partial matches such as finding forms filled out by multiple users. 
  1. Conceptual/Lexicon: Sensitive data can be identified in the unstructured data by combining the use of dictionaries, lexical rules, taxonomies, etc. However, this solution needs to be carefully customized for each organization.
  1. Statistical Analysis: Machine learning and other advanced statistical methods are used to identify policy violations and sensitive content. To achieve higher effectiveness, large volumes of data need to be added. 
  1. Categorization: DLP solution categorizes the data to detect highly sensitive data, violations of compliance regulations, PCI (Payment Card Industry) protection, HIPAA (The Health Insurance Portability and Accountability Act), etc. 

DLP Best Practices that strengthened the Data Security 

Prioritize and Classify the Data 

Every organization understands its own critical data. The first thing an organization has to do is to identify such critical data which needs to be protected at any costs against attacks or thefts. 

Classifying data by context is the simplest and most scalable approach. This means associating a classification with the source application, the data store, or the user who created the data. Applying tags to these users enables organizations to track their use. Content inspection can be beneficial as it comes with pre-set rules for PCI, PII, and other standards to easily identify regular expressions. 

Understanding when data is at risk

There is always risk associated with data that is being distributed among devices, partners, customers, and the supply chain. In such cases, the highest risk of data can be observed in the use of endpoints. Examples include attaching data to an email or moving it to a USB device. Having a DLP program in place will account for the mobility of data and when it is at risk. 

Monitor data in motion

Understanding the data usage and its behavior that involves risk needs to be monitored by the organization. Monitoring data has its importance such as visibility on sensitive data, determining the scope of the issues, and others. 

Communicate and develop controls

The following step should be to coordinate with managers regarding the cause and create controls to reduce data risk. DLP program at the initial stages may be simple. By having an understanding of the DLP program, organizations can develop focused and fined tuned controls to reduce specific risks. 

Train employees on the cyber security practices 

It is very important to educate and bring awareness to employees on the security policies and procedures. When educated, they understand the importance of data security and perform better. Penalties for breaching data security help improve clearly defined compliances.  

Why is DLP Important? 

2021 has been a significant year for cybercriminals impacting both MSPs and small businesses. The year witnessed many cyberattacks, including ransomware, malware attacks, and vulnerability exploitations. 2021 can also be described as the year when software supply chain attacks hogged the limelight. SolarWinds hack opened the world’s eyes to the impact of supply chain attacks, which was further emphasized during the year through the significant supply 

chain attack abusing Kaseya management software, Codecov coverage tool, and Log4j library.

As cyber criminals shift to more extensive, cross-border targets, we have seen a shift in tactics: moving to ever-larger organizations or business models that dictate how ransomware and other attacks occur.

Analysts, researchers, and security companies have been working quickly and constantly to identify and block emerging threats, but attackers have been just as quick in devising new tricks and tactics.

The DLP solution that you choose will work along with strategies to reduce risk. Risk can never be reduced by 100%, so DLP solutions detect sophisticated attacks that bypass your cybersecurity defenses. They also keep your environment compliant so that the organization avoids hefty fines for regulation violations.

Why do Organizations Need DLP?

A DLP solution can solve most of the cybersecurity and compliance challenges faced today. Having a DLP for your organization will help you with: 


It is now compulsory for many industries to have constant monitoring and data protection in place. Organizations that are needed to follow compliances such as HIPAA, PCI-DSS, GDPR, or any other standards can benefit from having a DLP solution. 

IP Protection

It’s not uncommon for organizations to store intellectual property in document files, and a DLP will stop attackers from accessing and stealing trade secrets.

Visibility into your data: Tracking data both at-rest and in-transit is a compliance requirement, and it helps organizations understand the types of data stored across endpoints.

Visibility into your data:

Tracking data both at rest and in transit is a compliance requirement, and it helps organizations understand the types of data stored across endpoints.

Why Micronova for DLP Solutions?

Micronova with the right set of tools has secured business-critical data for growing business. You can count on us for powerful, reliable End Point Security. We guarantee you peace of mind with expert protection, backed by a dedicated and friendly customer support team. With 39 years of business, Micronova benefits you with:

  • OEM and Partner Support
  • Price Advantage
  • Free Demo*

As an IT security Gold partner to Seqrite products, Micronova has tackled advanced cyber threats by providing comprehensive End Point Security services to multiple businesses. For inquiries, reach us at or +91 8147090194


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