What Is DLP? (Definition, Importance and Tips)

By Indeed Editorial Team

Published July 13, 2021

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Businesses today often rely on a digital and web-based infrastructure to get work done quickly and efficiently. With these conveniences, however, there are concerns about the security of the data that organizations store and handle. DLP is a type of software that can help organizations manage, track and secure their data, preventing data leaks and breaches by unauthorized users. In this article, we define DLP, examine how it can be useful and provide tips for its implementation.

What is DLP?

DLP is data loss prevention, which refers to software that protects sensitive data from theft, misuse or viewing by unauthorized end users. This protection applies to each of the three states of data:

  • At rest: data that is currently not being transferred or accessed by a user

  • In motion: data that is transferred between endpoints in a computer system or between separate computer systems

  • In use: data being read by a computer system because of updating, processing or accessing by a user

An organization can define a policy within DLP software to categorize specific data as confidential or critical. The software can then track the specified data, determine when attempted access or use of the data violates policy and enforce the policy through protective actions. For example, DLP in a hospital database of patient data would protect sensitive medical information, as required by HIPAA, authorizing access only by certain medical professionals. In the event that an unauthorized user tried to access this data, the DLP software might encrypt the data and alert the network administrator to prevent misuse.

There are three categories of DLP:

Standard security

Standard security refers to common products or means for protecting computers from unauthorized access firewalls. These include:

  • Firewall: prevents users outside of a network from accessing data within the network

  • Antivirus program: internally scans a computer for malicious programs that can compromise the data within or the network as a whole

  • Intrusion-detection system: monitors activities and on-screen events within a computer system to ensure that unauthorized end users aren't trying to access confidential data

Related: Cyber Security Specialist Interview Questions (With Sample Answers)

Advanced security

Advanced security entails algorithms and machine learning that can identify abnormal or suspicious behavior within a computer system. These include:

  • Honeypot: easily obtainable data that falsely presents itself as valuable or sensitive, luring hackers and recording their information when they try to access this data

  • User-activity monitoring: ensuring that employees and contractors are staying within their assigned tasks

Designated systems

Designated systems can identify when a user is trying to duplicate or transfer confidential or sensitive data and prevent these activities from occurring. This level of protection is important for safeguarding against end users with authorized access to the data, who might otherwise compromise data security without meaning to do so. An example of a protective mechanism for designated systems structured data fingerprinting, whereby algorithms map files into smaller text strings called fingerprints, which act as unique identifiers for the data. The DLP system can then scan any in-use or in-motion files for fingerprints to protect against data leaks.

Purposes of DLP

DLP software serves three major purposes:

Compliance

Organizations that collect and store personally identifiable information, or PII, from clients, customers, users or patients are responsible for protecting the data. Such data includes:

  • Protected health information: Protected health information, or PHI, refers to any information relating to health and medicine that can identify a patient, including names, medical histories, insurance information, certain geographical identifiers, contact information, social security numbers and photos. Hospitals, clinics and health insurance companies store PHI and must protect it per HIPAA guidelines.

  • Payment card information: Also known as PCI, payment card information is data related to payment cards, such as the names and numbers on an individual's credit or debit cards. Retail organizations often store the payment card information of their customers.

These organizations may use DLP software to classify the protected data to prevent leaks or access by unauthorized parties. The software may also include reporting functionality, which can be useful for generating documents that prove compliance with data protection regulations.

Data visibility

Visibility refers to knowing where specific data lives within a computer system, how it moves and what users access it. This knowledge allows you to determine whether anyone is interacting with the data in unauthorized ways. DLP software allows you to track classified data within various environments, including networks, individual computers and the cloud.

Protection of intellectual property

Intellectual property is an intangible asset created from intellect or imagination, such as trade secrets and patents. For example, a company that produces kosher salt might have a proprietary manufacturing process that produces uniform, flat salt flakes that stick well to food. Being the only organization with knowledge of this process allows the company to produce a high-quality product relative to competitors.

Thus, it's important to protect such intellectual properties because they can give your organization a competitive advantage over others. With DLP software, you can implement policies around data that contain sensitive information about your intellectual properties to prevent unauthorized copying and extraction by competitors.

Related: Intangible Assets: Definition and Examples

Reasons to use DLP practices

Many organizations use DLP solutions to protect their data, and the DLP market appears to be growing. There are several reasons for this increasing adoption of DLP practices, including:

Prevent data leaks and breaches

Competitors seeking trade secrets and individuals out for financial gain often target the sensitive data stored in corporate databases. These data leaks and breaches can be costly and jeopardize the privacy of users' personal information, so it's important to have safeguards and security measures in place. Thus, organizations have adopted DLP practices, which can prevent or mitigate instances of data compromise.

Related: 16 Jobs in Cybersecurity To Consider Today

Adapt to changes in regulations

Regulations surrounding data protection often change in response to large data breaches and leaks. For instance, in 2020, the U.S. Senate passed the Internet of Things Cybersecurity Act, which establishes minimum security standards for internet-connected devices used by the government. Having a DLP system in place would help organizations to adapt to such new regulations quickly and smoothly.

Protect valuable data

As businesses and business practices have evolved over the years, so has the definition of valuable data. Today, it's not just product information and trade secrets but also business and marketing strategies that are considered valuable. As a result, many organizations now have more data that's in their interest to protect, and DLP helps them to protect it.

Keep data storage points safe

Many businesses allow employees to use their own devices at work, and each personal computing device is a storage point for data. A larger number of personal computers at work increases the possibility that an employee may accidentally share data with unauthorized users, so it's important to implement a DLP solution to prevent the movement of sensitive data into personal devices.

Cloud-based services are another common storage point that can compromise data security. For example, if a user moves a file away from an organization's network and into a cloud database, unauthorized users could more easily access the data within the file. Again, DLP software can track the movements of sensitive data and prevent compromise.

Handle records efficiently

CISOs are chief information security officers, an executive responsible for maintaining the security of an organization's technology and data. CISOs typically work closely with CEOs, reporting on strategies for data protection and plans for handling data compromise. DLP software is helpful to CISOs since it can show important details such as end-user behavior and data movement, and it often features reporting functions that can easily provide updates about the state of an organization's cybersecurity.

Related: How To Become a Chief Information Security Officer

Tips for effective DLP

Consider these tips to implement an effective DLP system:

Familiarize members about DLP policies

Educating the members of your organization about policies surrounding the DLP system can complement the software capabilities and increase security. If possible, try to involve employees, managers and other stakeholders in an orientation that familiarizes them with best practices to prevent accidental data sharing and unauthorized data movement. Avoiding compromising circumstances can remove the need for additional security measures.

Work on continuous improvement

Blocking or restricting certain data can sometimes affect business operations. For example, if several employees need to examine customer PII to provide customer service, restricting access is likely to reduce productivity and efficiency. In such instances, try to collect feedback from end-users so you can fine-tune the DLP system for balanced security and accessibility.

Determine key performance indicators

Key performance indicators, or KPIs, are metrics for determining the success of an operation or individual. In this case, try to determine KPIs that indicate whether your DLP system is successful. For example, you might aim to achieve a low response time to DLP alerts and minimize the amount of unclassified data. These KPIs can serve as both an assessment of the system's effectiveness and targets toward which to aim.

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