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Data Loss Prevention Policy Template: How To Create a Data Loss Prevention Policy

by Chris Brook on Tuesday May 30, 2023

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Implementing a DLP policy can help put safeguards around data in your organization. In this blog, we walk you through the steps to creating an effective DLP policy, including how to outline specifications around data classification, handling, and discovery.

The data your organization collects and utilizes to power daily operations is vital, and the loss of data can often have an immediate impact on your ability to conduct business and protect your interests. As operations scale, the importance of their data does too, and the risks posed by lax security surrounding such information increase in severity.

Implementing a data loss prevention policy puts solid protections in place at key levels of your organization's infrastructure, ensuring crucial information is kept secure at all times.

Although keeping data in silos with strict access management may be the most secure approach to managing your organization's information, it limits your data's utility. Now, more than ever, data has moved from silos to distributed networks and a wide variety of platforms, as decision-makers seek to make better use of the intel their organizations have gathered. 

Keeping your data safe without hindering growth and real-world usability is a delicate and complex balancing act. It’s something you’ll need to perfect to succeed, and a data loss prevention policy is essential for accomplishing all of the above.

This article will cover all the main parts your data loss prevention policy should include in order to be effective.

What is a Data Loss Prevention Policy?

A data loss prevention policy is a set of rules governing the use and exchange of sensitive internal data. Organizations follow data loss prevention policies when interacting with the sensitive information they control.

We’ll go over each of the key details you should include to make your data as safe as possible, whether it is at rest or in motion. Sections governing access to data, authentication of users, usage reporting, and more are described below. 

We also touch on some of the challenges involved in keeping data secure once your preventative policy is in place.

Data Loss Prevention Template Sections

Data loss prevention policies make it easier to ensure that only authorized personnel can access data in safe ways, preventing accidental deletion, exposure, corruption, or manipulation. Here are the sections you should include when creating a preventative policy of your own:

Data Classification

Classifying your data by its relative sensitivity is the very first step you should address in your data loss prevention policy. This is especially true when it comes to establishing what constitutes confidential information, as it can help to make priorities clear across your organization. Separate tiers can then be drafted for less sensitive data and general access requirements.

Data Handling

Specifying precise protocols for accessing and interacting with valuable internal data is a must for every data loss prevention policy. Setting up a simple matrix in which data types and their transmission mediums are paired with authorization requirements is a great place to start when defining your data handling requirements.

Data Discovery

This section of your policy deals with the different measures you intend to take to keep track of potentially sensitive data as it is accessed and transmitted. Data discovery makes it possible to stop sensitive information from leaking via common weak points like emails and messaging systems. 

Outlining not only how data can be exchanged but also what systems must be implemented to detect it is essential for this portion of your policy.

Data Loss Prevention Policy Best Practices

Crafting the perfect data loss prevention policy goes beyond including the right sections. Here are a few important best practices to adopt during your policy's drafting process:

Avoid interrupting important activities

Taking steps needed to comply with your predefined data loss prevention policy should ideally never affect day-to-day business within your organization. Whether your policy calls for regular backups or strict authentication, company-wide needs must be accounted for. 

A practical example of defining these types of requirements in a manner that matches your organization's needs might be scheduling database backups for off-hours or periods of relatively low network activity.

Focus on your most vital data first

Although your organization should ultimately strive to develop and fully implement a data loss prevention policy that protects all your data at all times, it is likely easiest to start closer to home. Data that you depend on to keep operating should be protected first. By concentrating your efforts on key intel in the beginning, you guarantee yourself a firm foundation for future preventive efforts to be based on.

Adopting a modular approach to data loss prevention makes this much easier to manage. Instead of developing a single, comprehensive policy for all facets of your data infrastructure, you can concentrate on individual platforms, processes, or data sources at a given time, defining security practices for these independently.

Securing data within your organization starts with setting up an appropriate data loss prevention policy. Your policy must be drafted with your own unique infrastructure and interests in mind for it to be effective.

 

Tags:  Data Loss Prevention Data Classification

Chris Brook

Chris Brook

Chris Brook is the editor of Digital Guardian’s Data Insider blog. He is a cybersecurity writer with nearly 15 years of experience reporting and writing about information security, attending infosec conferences like Black Hat and RSA, and interviewing hackers and security researchers. Prior to joining Digital Guardian–acquired by Fortra in 2021–he helped launch Threatpost, an independent news site that was a leading source of information about IT and business security for hundreds of thousands of professionals worldwide.

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