What Are Data Loss Prevention DLP Best Practices?

What Are Data Loss Prevention DLP Best Practices?
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The world in the current age revolves around data. In the contemporary world, people process or generate data in almost every endeavor of their lives. The data processed by users has increased exponentially over the past few years. In 2018, the total data consumed worldwide was 33 Zettabytes. This figure rose to 59 Zettabytes by 2020 and is predicted to reach over 175 Zettabytes by 2025. All this is to say that the amount of data used increases significantly as the years go by.

If these statistics are anything to go by, life in modern times revolves around data. For this reason, humanity should pay attention to how the data they periodically generate is used, stored, and manipulated. Data loss prevention strategies provide a suitable framework for properly conducting data.

What is Data Loss Prevention?

In simple terms, Data Loss Prevention, or DLP, is a set of policies, protocols, and software that guarantees the proper usage and manipulation of data. This extends to efficient DLP Data Loss Prevention Assessment. These strategies provide a framework for any organization to avoid data loss and breaches. Thus, the essential functions of an efficient DLP framework are as follows:

  • Ensuring that data is stored safely in all stages of manipulation, whether in transit or its final destination.
  • Monitoring the movement of data to ensure that there is no unauthorized access to proprietary information.
  • Preventing vulnerability in data processing either through data breaches or unintentional disclosure of sensitive information.
  • Auditing data usage and fixing possible weak points in the data processing.

What is Data Loss Prevention?

Technical Approaches to Data Loss Prevention

There are two main technical approaches to DLP:

Content Analysis

This involves considering the content of data to consider how to classify it. The information considered in content analysis is the basic metadata in the document’s header. The classification of data informs what DLP mechanisms are best placed around it. Different kinds of data require varying degrees of DLP. Thus, to avoid the wastage of resources over data that has inconsequential worth, it is crucial to classify data to ensure that resources are only spent on sensitive data.

Content Awareness

This step further goes to evaluate the document’s or data sources’ specific contents to consider whether the data in question has sensitive information. It varies from the content analysis since it considers everything in the data context, rather than simply evaluating the metadata and judging from that information.

While many modern DLP software incorporates content awareness and analysis, content awareness is the bulk of the fold. Standard techniques in content awareness include rule-based analysis, dictionaries to evaluate common phrases indicating sensitive information, data matching, and statistical analysis.

Content Awareness

What to Consider When Building A Data Loss Prevention Policy

While the specifics of every DLP policy vary from organization to organization and based on the specifics of the organization’s needs, there are some common considerations every organization can have in its attempts at instituting a proper DLP policy.

First, you must identify the critical elements of your organization’s data processes. Some DLP experts refer to this as the crown jewels of the organization. Securing the crown jewels is paramount as data breaches of the crown jewels could lead to crippling the organization.

What to Consider When Building A Data Loss Prevention Policy

Once you have identified the crown jewels, you must ensure that every individual in the organization has specific roles where DLP is concerned. Defining roles provides no overlaps or gaps where unscrupulous persons can create and exploit possible vulnerabilities. Additionally, defining the roles every individual plays in processing the data ensures that it is possible to identify potential breaches and fill them in advance regarding data auditing and auditing the DLP system.

Automation plays a critical role in DLP. Where the human aspect is absent from the equation, it is possible to have an efficient DLP framework. Human error is one of the most significant contributing factors to data breaches. A study by IBM identified that humans cause at least 95% of all data breaches. Thus, to avoid the possibility of data breaches crippling your organization, automating all the processes surrounding DLP is essential.

Additionally, automation increases the quantity of data that the DLP framework processes. Manual processing can only cover a limited amount of data at any given time and requires counterchecking to ensure that everything is in proper shape. However, with automated DLP, data processing is expeditious and efficient.

Parting Shot

As you begin to put in place the DLP framework of your organization, it will be essential to ensure that all the expectations people have concerning data processing are available upfront. In organizations, DLP policies should be part of the onboarding processes of every new hire. It should also form part of the organization’s regular training mechanisms. With this, you will have a comfortable experience with the data you process.


Information misfortune avoidance settles three primary goals that are normal trouble spots for some associations: individual data insurance/consistency, licensed innovation (IP) security, and information perceivability.

Individual Information Protection/Compliance: Does your association gather and store Personally Identifiable Information (PII), Protected Health Information (PHI), or installment card data (PCI)? Assuming this is the case, you are undoubtedly dependent upon consistent guidelines, like HIPAA (for PHI) and GDPR (for individual information of EU occupants) that expect you to safeguard your clients’ delicate information. DLP can distinguish, group, and label touchy information and screen exercises and occasions encompassing that information. Moreover, revealing abilities give the subtleties expected to consistent reviews.

IP Protection: Does your association have significant licensed innovation and exchange or state insider facts that could seriously endanger your association’s monetary wellbeing and brand picture whenever lost or taken? DLP arrangements like Digital Guardian that utilize setting-based characterization can order licensed innovation in both organized and unstructured structures. With approaches and controls set up, you can safeguard against undesirable exfiltration of this information.

Information Visibility: Is your association looking to acquire extra perceivability into information development? An extensive venture DLP arrangement can help you see and track your information on endpoints, organizations, and the cloud. This will give you perceivability into how individual clients inside your association interface with information.

While these are the three fundamental use cases, DLP can remediate an assortment of other trouble spots, including insider dangers, Office 365 information security, client and element conduct investigation, and high-level dangers.

Thank you for reading!

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