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May 28, 2020

Data Loss Prevention (DLP) Myths Putting Your Company At Serious Risk

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Image courtesy of (Stuart Miles) / FreeDigitalPhotos.net

Security at any level is important for a company. Nearly every month there is a news story covering a data breach. In 2020, many top companies have fallen prey to cybercriminals. Data breaches have affected Microsoft, T-Mobile, MGM Resorts, Walgreens, and J. Crew.

And don’t think smaller companies are exempt. The public just doesn’t hear about those data breaches as much, since they are not as newsworthy. This makes data loss prevention (DLP) a must for any company.

Data loss prevention covers a number of strategies in order to protect companies from cybercriminals. However, many companies are still not fully adopting DLP, or not making DLP a priority. You can learn more about data loss prevention via this ultimate guide by Proofpoint.

Let’s focus on the “why” when it comes to companies failing to adopt DLP strategies. In most cases, the myths surrounding data protection act as deterrents for adoption. Here are a few DLP myths that may be putting your company at serious risk. 

The Company’s Network Will Lag

This is one of the most common data loss prevention myths out there among company executives and IT administrators. Latency is possible when analyzing all network traffic in order to identify sensitive data. However, DLP does not need repeated content inspection.

Data loss prevention can be used to classify data as it is developed and modified. This is done via content inspection with contextual and user classification. Tags are added and endpoint controllers will see these tags, thus classifying usage rules. This gives your company maximum visibility without the network lag.

Integrating DLP Is A Massive Company-Wide Effort

This is another myth worth busting when it comes to data protection. Yes, your company can integrate DLP in one major shift, but it isn’t all that necessary. In most cases, integrating DLP slowly with a focused approach can be more beneficial. 

For instance, your company can choose a data category that is the most sensitive. You identify this data category as a DLP pilot and focus on it until it is completed. Once the framework is set up, you can add more data categories at scale. This allows a company to shift slowly into DLP without issue.

Content Analysis Is Too Complicated

This myth couldn’t be further from the truth. Content analysis identifies and examines files by looking at patterns. For example, credit card numbers or social security numbers. DLP may not require this for your company.

DLP may use content analysis with simplified terms, allowing your company to use DLP to classify data automatically. This can speed data loss prevention adoption and keep privacy of communication at the forefront. 

Applications used to develop data, users that developed the data, the location of the data, and other set qualifications of content analysis can all be used by DLP programs for a streamlined content analysis process.

DLP Is Only For Internal Networks

This is another common data loss prevention myth putting your company at serious risk. It is very true that DLP is great for a company’s internal network. However, many believe that externally it doesn’t work, or work as well. 

Data loss prevention works anywhere, from outside of a company’s network to virtual environments. This is because DLP applies protection to the actual data, not a device, network, or user. By applying DLP at a data level, sensitive data is automatically prevented from exiting your company’s network. 

The only way data that has been protected by DLP can leave your company’s network is by setting up approved devices, as well as encrypting any data that is sent outside a network. These permissions and devices are set up by your team, and permissions can be changed as needed.

Data Loss Prevention Measures Will Decrease Productivity

DLP applied at the data level does not affect real users that follow the corporate data policies your company has in place. This is because endpoint agents classify data and set transparent policies to be enforced. DLP can certainly be used in non-intrusive ways in order to keep production at optimal levels.

For example, warnings that prompt users that risk is possible can be employed, thus reinforcing security policies of the company. This simple application of DLP can help keep data safe while ensuring employees get the most productivity.

Wrapping Up . . . 

The above data loss prevention myths need to be dispelled in order for your company to adopt DLP for maximum data protection. You definitely don’t want your company to join the many that have had data breaches this year. Take action and stay proactive when it comes to protecting your company’s data from cybercriminals. 


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