Building a data loss prevention (DLP) solution with data discovery, classification, and remediation capabilities

Data loss prevention (DLP) is critical for any organization that collects, stores and uses sensitive data. Data loss occurs when data is accidentally deleted or is compromised, which can happen for a number of reasons. Data breaches, cyber hackings and viruses are a few well-known examples.

However, preventing data loss doesn’t always entail combat with a corrupt, external source. A very common cause for data loss is unintentional human error from employees—which doesn’t come from a place of malicious intent. This can be something as simple as accidentally sending an email to the wrong recipient. Data loss can also occur due to unpredictable, and something unavoidable, physical damage to hardware, like liquid spills, natural disasters, or power outages.

When important files and documents are lost—especially sensitive data—your company’s day-to-day operations are considerably disrupted. Valuable time and resources are spent either recovering or recreating lost and corrupted files—sometimes, to no avail. And in the case where a data breach is involved or the cause of data loss, your organization has even greater consequences to deal with. There’s the notification of the breach to affected customers, potential reputational damage, the possibility of legal and compliance fines and more.

With this in mind, it’s important to choose an enterprise DLP solution that can help you get ahead of your risks and protect against emerging threats. Here’s what to look for in a DLP solution and the three key capabilities for the best DLP coverage.

Why do organizations need a DLP solution?

A DLP solution can discover protected data on desktops and laptops, classify that data based on risk level, and then remediate the data by applying policies designed to mitigate potential risks. It’s often considered a key element of an organization’s information security strategy because it provides protection against aforementioned threats, such as human error, malware or hacking.

Data loss of any kind can be costly to an organization with the amount of time and resources it often takes to recover data. By implementing a DLP solution, companies can save time and money on these efforts, allowing security teams to focus on areas that truly need attention, becoming proactive rather than reactive. A comprehensive DLP solution will also help with:

  • Protecting personally identifiable information (PII): PII is sensitive data that can be used to identify a particular person, such as social security numbers, driver’s license numbers, email addresses, home addresses, bank account numbers and more.
  • Ensuring regulatory compliance: There are several compliance regulations that protect consumers’ sensitive data, like HIPAA, GDPR and CCPA.
  • Safeguarding intellectual property: If your organization has intellectual property, highly confidential information or trade secrets, you don’t want to risk that data being lost or stolen.
  • Better data management: A DLP solution can give your security team full visibility into where your data lives, where it moves and who has access to it.

What to look for in a DLP software solution

Sensitive data monitoring capabilities

Generally, a DLP solution will monitor sensitive data at rest, in motion and in use.

Data at rest

Just as the name suggests, this is data that’s stored and not currently being used. Oftentimes, data may end up being saved in areas that teams are unaware of. Some organizations will end up storing sensitive data for longer than needed, but don’t have the full view of all their data at rest, since it’s flying below the radar when it’s sitting still.

Data in motion

Data in motion is a term used for data that’s in the process of moving through a channel or network endpoint. Important details to look for in data in motion includes who initiated the data transfer (do they have authorization?) and where that data is headed.

Data in use

Also straightforward, this term describes any data that’s currently opening in an application or software.

Core data discovery and classification features

At minimum, your DLP solution should include features that help discover and classify data at rest, monitor data in motion and remediate based on data activity. Organizations should also consider the following when searching for the best DLP software solution:

Real-time monitoring and analytics

When it comes to sensitive data, you need to be agile. Look for DLP solutions that offer real-time alerts or notifications, so your security team can act fast if immediate action is required. Real-time analytics and reporting will also make it easier for your security team to keep a watchful eye on sensitive data security, and assess the solution’s performance. When reviewing this feature, assess whether the reports and analytics are easy to digest. It’s not just the data reported to your team that’s important—the way that data is presented makes a big difference. Does it take time to decipher, or can you instantly understand the reports at a glance? Automated data visualization makes this process easier.

Automated workflows

Your organization’s data policies and procedures are the backbone of any DLP solution you choose. Your DLP solution should offer automated workflows that make it easier to carry out those policies. For example, if you have a certain procedure your team wants to implement for data that is classified as “internal,” an automated workflow would allow you to enable trigger actions and if/then logic to eliminate manual work and the potential for human error.

Tech stack integration

Does your DLP solution play nice with the other technologies in your company’s stack? Will it work multiple endpoints, on both the cloud and on-premise tools? As robust as a DLP solution is, it’s likely not going to be the only security software your team has in place. You’ll want to ensure that your technologies can “speak” with each other to improve your team’s overall efficiency and threat detection. When your security software exists in silos, you leave gaps for threats to slip by.

Three key capabilities for comprehensive DLP coverage

When looking at the most sought-after features in a DLP software solution, you’ll see that there are three key capabilities that make it all happen: discovering sensitive data on the network, classifying it based on its type (i.e., whether it’s personal or confidential), and fast-acting remediation.

1. Sensitive data discovery

Discovery is key to achieving a strong hold of all your data at rest, and truly serves as a foundation for DLP coverage. How can you prevent data loss if you don’t know the data exists? When choosing DLP software, consider how strong the solution’s data discovery capabilities are. How quickly does it discover sensitive data? Is it a matter of days or minutes? Can it discover sensitive data across multiple endpoints from on-premise to the cloud? These are important considerations when vetting a software’s data discovery capabilities.

2. Data classification

An organized system is a more efficient system. Classifying your data makes creating automated workflows easier, since you can build those workflows based on the data’s level of sensitivity. It can also make viewing analytics at a glance easier. Instead of looking at all of your data, you can zoom in and view data that falls underneath a specific classification.

3. Data remediation

To prevent data loss, your DLP solution should be able to do more than just monitor—it should also be able to act and remediate. This includes replacing, modifying, cleansing, or deleting any data as deemed necessary.

Protect your sensitive data with data loss prevention software

The Spirion Sensitive Data Platform offers a data loss prevention integration that is designed with the three key capabilities discussed as the backbone of our DLP solution. To learn how you can build a comprehensive data loss prevention solution, get a free demo here.

1