7 Best Practices for Data Loss Prevention

Most organizations have at least one thing in common: they generate and consume more and more data yearly. Dealing with all this data can be overwhelming, especially for those organizations that haven’t fully embraced the digital transformation and the cultural shifts that come with it.

As your data grows, so does the risk that your data will be exposed to unauthorized parties in a security incident called a data breach or a data leak. Today, data breaches are one of the most severe cybersecurity threats faced by organizations worldwide. Likely, the number and frequency of these events will only continue to soar in the coming years.

Data risk management is the process your organization uses throughout the data lifecycle to enforce data security and eliminate data risk. From creation to retirement and during acquisition, transformation, and usage, a data risk management program ultimately works to keep your data safe from internal and external cybersecurity threats.

One of the most important components of a successful data risk management program is Data Loss Prevention (DLP), a set of tools and processes to ensure that your organization’s sensitive data isn’t lost, misused, or accessed by unauthorized parties.

In this article, we’ll look at data loss prevention, discuss why it’s essential, and introduce some of the best practices for creating a DLP strategy and policy that protects your organization’s most sensitive data from cybersecurity threats.

What is Data Loss Prevention?

Almost every organization creates, transmits, and stores sensitive data. Sensitive data is information that must be protected against unauthorized access to safeguard the privacy or security of an individual or organization. This data might be intellectual property, databases, or entries on a spreadsheet containing Personally Identifiable Information (PII).

While PII, like names or birthdays, might not seem incredibly important to protect, they can be used by malicious actors to steal the identities of those whose PII was exposed. PII can also contain sensitive information, such as social security and driver’s license numbers, you wouldn’t want on the dark web. PII can belong to your employees, customers, or stakeholders; sometimes, it’s protected by law.

For example, the European Union’s General Data Protection Regulation (GDPR) protects consumers’ personal information in the EU, and the California Consumer Privacy Act (CCPA) protects the personal information of consumers who live in California.

These data privacy laws, and others, protect consumers from having their data unintentionally leaked or lost due to a malicious actor, insider threat, or unknowing employee. When an organization falls victim to a data leak or data breach, it usually results in significant financial loss, reputational damage, and any regulatory and legal consequences.

The average cost of a data breach was $4.2 million in 2021. While most money usually goes toward repairing reputational damages and loss of business, a lot goes toward paying the hefty non-compliance fines associated with the above regulatory and compliance standards and more.

Unfortunately, even with regulatory and compliance standards in place, it often takes organizations a long time to identify a data breach has occurred – about 197 days, to be exact. Even those organizations that do catch data leaks early often can’t do much about it because it’s already too late.

This isn’t good news for consumers. In 2021 alone, more than 281 million people were affected by some sort of data breach, surpassing the total number in 2020 by 17 percent. As more consumers are influenced by data breaches resulting from organizations’ poor or nonexistent data loss prevention strategies, their expectations about data privacy will only continue to increase. Organizations that want to stay relevant must prioritize DLP and transparency if they remain in business.

While most cybersecurity strategies to prevent data breaches focus on addressing external security threats like malware and phishing attacks with firewalls and antivirus software, data loss prevention strategies focus on addressing internal threats such as a disgruntled or negligent employee. Many organizations simply don’t realize or want to acknowledge that these types of insider threats can pose severe risks to their business.

Meanwhile, insider threats account for nearly 60 percent of all data breaches. For this reason and more, your organization needs a DLP strategy to help you detect and prevent potential data breaches by monitoring, detecting, and blocking sensitive data while in use, in motion, and at rest.

Types of Data Loss Prevention

Generally, there are four types of data loss prevention: endpoint DLP, storage DLP, network DLP, and cloud DLP. Your DLP strategy should address each of these types of DLP to ensure the security of your data.

• Endpoint DLP (data in use): this includes data residing on devices such as desktop computers, laptops, USB storage devices, or virtual desktops.
• Storage DLP (data at rest): this is usually unstructured data residing on a server or structured data residing on a database.
• Network DLP (data in motion) includes data that transits or leaves the network to the Internet, including emails.
• Cloud DLP includes data residing on the cloud or in personal email providers.

Which types of DLP you choose to prioritize will ultimately depend on your organization’s specific needs and should inform any decisions you make regarding which DLP solutions you select to automate parts of the process.

DLP Solutions

Ideally, your DLP strategy should integrate DLP tools, including DLP software, with a holistic program to protect your data from internal threats throughout your organization. This means you’ll need to create a DLP policy tailored to your business needs and address the added challenge of selecting the best DLP solution to help you implement and maintain your data loss prevention program.

Regarding DLP software, the core components haven’t changed much in the last few years, except cloud computing. Most DLP solutions are designed to discover and analyze the content and the context of your organization’s data to determine if it matches a pattern or expression. Once a pattern is reached, the software will generate and send a violation notification or alert to management for review.

Which patterns you define will depend on the types of data you’re most concerned with protecting. Still, it often includes easily recognizable data like social security numbers, credit card numbers, HIPAA terms, keywords, or any other alphanumeric patterns you want to define.

Most DLP solutions also utilize fingerprinting, which is performed by algorithms that map data to shorter text strings to create unique identifiers for their corresponding data and files- much like the human fingerprints used to identify individual people. Fingerprinting is especially useful for organizations that identify sensitive data within forms.

DLP products use a discovery engine that crawls your data, indexes it, and makes it accessible through an intuitive interface. This allows for quick searching for data, including information about its sensitivity and ownership.

Later, we will discuss in more detail how you should choose a DLP solution that supports your DLP strategy and can easily integrate with your DLP policy. Next, we’ll introduce some of the most common data loss prevention mistakes and how to avoid them.

Most Common Data Loss Prevention Mistakes

When it comes to DLP, a lot can go wrong. First and foremost, many organizations simply don’t understand that a DLP is intended to restrict the flow of information both internally and externally. Ultimately, this will categorically impact how business is done.

It’s a classic risk vs. reward situation: don’t implement DLP and face the risks, or do implement DLP and meet different types of risk. In most cases, implementing DLP outweighs the risk of not implementing DLP, and many organizations find that any business interruptions a DLP program might introduce are worth it in the long run.

While most organizations want to implement a DLP strategy, some security experts suggest they rarely make it to the blocking phase. This is because there is often too much focus on acceptable tuning DLP policies and procedures to eliminate false positives and insufficient actual blocking. Organizations implementing DLP can spend months or even years working to ensure that their DLP program only generates valuable information.

Today, most organizations generate insurmountable amounts of sensitive information, so you must decide which data to protect. Cast too broad of a net, and you’ll likely have more false positives. But cast too narrow of a net, and you’ll only be able to address one specific business area, leading to much-missed content.

Organizations with a DLP strategy must understand that there are better ways to stop data loss than DLP. It just isn’t designed to stop intentional leaks. But, it can help you find out about them.

At its core, DLP mainly acts as a deterrent for your staff and any other internal actors to let them know that you’re closely monitoring specific types of activity. There will likely be a noticeable decrease in threatening internal activity simply because people know you’re watching.

Now that you understand DLP better, why it’s essential, and some of the most common mistakes organizations make when implementing it, it’s time to introduce some of the most important best practices when creating and maintaining a DLP strategy for your organization.

Creating the Best Data Loss Prevention Strategy

Unfortunately, there isn’t a one-size-fits-all approach to data loss prevention. What you choose to monitor and how you choose to address DLP will ultimately depend on your organization’s specific needs. However, some data loss prevention best practices can be applied to any DLP strategy, regardless of your organization’s unique business processes.

Pick the Right Team

As with any business program, the first step is to ensure that you have the right people to put the technology in place and carry out the necessary processes. Who you put in charge of your DLP program will drastically affect the program as a whole, so choose wisely.

Start by creating an internal DLP committee composed of senior leaders, business unit managers, legal, and infosec management. Each party clearly defines its role and responsibilities in the DLP strategy. Specify who owns which data, which IT security officers are responsible for which aspects of security incident investigations, and so on.

Start with a Plan

This is where you’ll start to develop your DLP strategy, but before you put that strategy into writing with a DLP policy. A well-thought-out plan can mean the difference between failure and success, so put as much time and effort into this step as necessary.

Start by identifying your proverbial crown jewels, the most critical data your organization owns. This could be intellectual property, PII, or other sensitive information you must protect at all costs.

Then, you need to define your metrics. DLP is an excellent system to show how much data is getting flagged and where the most significant issues are, but before you get into data analytics, you need to decide what you’re monitoring for. Think about your business goals: what’s essential to your organization?

It’s important not to try to boil the ocean here. Go for small wins instead of aiming to check off every single policy available. Ultimately, you don’t want to overwhelm your system with massive incidents.

At the very minimum, here are the basic parameters you should define:

• Which organizational data needs to be protected.
• Where that data resides.
• The conditions for accessing different types of data.
• Actions to be taken in case of information security incidents.
• What information is to be archived, and when?
• Any threats to your data.

Build Out Your DLP Strategy

You’ll need to start with data identification and classification to identify some of the abovementioned parameters. Ultimately, before you protect your data, you need to know what critical data you have and where it lives.

Using data discovery technology to scan your data repositories and report on any findings will give your organization visibility into what you need to protect. Together, data discovery and data classification technology help organizations control user data access and avoid storing sensitive data in insecure locations, which can reduce the risk of data leaks and data loss.

You should also put strict controls in place to prevent users from falsifying classification levels. Access control lists (ACLs) are lists of who can access what resources and at what level. ACLs are often based on whitelists (allowed actions) or blacklists (prohibited actions).

Consider using encryption for critical business data at rest or in transit to keep your data safe. Securing all the places where sensitive data could reside, even temporarily, will help prevent breaches or leaks without a DLP policy. Finally, your organization should avoid saving unnecessary data at all costs.

A rigorous patch management strategy is also essential to data protection and cybersecurity. Patch management will help your organization ensure that all your operating systems and applications in your IT environment are current. Patches for critical infrastructure should also be thoroughly tested to ensure that no functionality is compromised and no vulnerabilities are introduced into the system.

Create Practical Policies and Procedures

Once you have a team, a plan, and a DLP strategy, it’s time to put it into writing with a DLP policy. This is where things often get tricky for organizations. Putting a DLP policy into place means finding the right balance between being too restrictive and too loose.

For example, suppose part of your business process involves one employee sending sensitive information to another employee. In that case, you’ll need to ensure there are ways to do this securely. If you’re going to replace old procedures with new ones, you need to make sure that they’re going to work for your employees and that they’re going to follow them.

After you create your DLP policy, you’ll want to test it. Conduct a proof of concept exercise to replicate functionality and test feature sets. This stage can be compared to a pilot test to ensure your policy and technology will meet your compliance needs and observe the deficiencies in your triage process.

Educate End Users

As mentioned above, simply letting your employees know you’re watching is often enough to deter intentional internal threats. Any successful DLP program should begin with an educational program. Your employees and stakeholders are much more likely to understand and accept any changes brought about by your DLP program if you tell them why it’s essential and what’s at stake.

Data loss often results from simple end-user mistakes, i.e., sending credit card info via email or losing a USB storage device containing sensitive information. In these cases, end users often don’t know they’re doing anything wrong. Sometimes, internal threats are made up of malicious actors, but DLP will likely deter many of those actions. The more protections you have, the less likely you will be targeted.

Shift the Culture

A successful DLP strategy will necessitate a cultural shift, as with most programs. You will likely require end users to take different actions than they’re used to, so there will be a learning curve. Teaching an old dog new tricks can be challenging, which is becoming especially apparent with cloud storage.

Unfortunately, many DLPs die when senior executives don’t support the cultural shift that comes along with them. A top-down approach means engaging executive and senior leadership to direct the DLP program by providing input on what’s critical to your organization.

In the end, if you make severe changes to business processes due to DLP, you also need to provide your employees with solutions to replace those no longer considered secure processes.

Monitor and Repeat

As part of your DLP program, you must regularly inform stakeholders of its state. Holding monthly or quarterly meetings will provide you with additional input to help continuously drive the program and ensure the quality of the investment is operating optimally.

Ultimately, the more DLP processes that can be automated, the better. That’s why choosing the right DLP solution is critical.

Choose Tools to Help

Implementing a DLP platform can be expensive. You should be sure that the capital investment is based on a sound cost-benefit analysis, risk assessment, and vendor assessment. Once you’ve determined how much you can afford, you should define your expectations for DLP software and start looking for vendors that meet your requirements.

Start by researching multiple vendors, and think about consulting with peers in your industry to find out who they use for DLP to gauge their satisfaction with support, incident workflow, and overall confidence level.

Which DLP software you choose will ultimately impact which data will be protected. For example, if your organization doesn’t manage unstructured data on-premise or in the cloud, it probably wouldn’t be wise to invest in an expensive enterprise DLP solution that offers an entire suite of DLP features.

Best practices for Data Loss Prevention (DLP)

Implementing an effective Data Loss Prevention (DLP) program requires careful audits, security policies for classifying data, and incident response plans for cyber attacks. Follow these best practices to help safeguard messaging apps, authenticate users, and protect confidential and financial data from hackers:

• Classify your data: Categorize data by sensitivity level per PCI DSS standards and establish Microsoft Windows permissions and policies to restrict unauthorized user access based on classification. This allows you to prioritize protection for your highest risk of data loss information.
• Discover where sensitive data resides: Scan databases, file shares, email systems, and endpoints to locate where confidential data is stored. Understanding real-time network traffic flow is critical to detecting suspicious activity.
• Establish user access controls: Permit access to sensitive data on a strict need-to-know basis aligned with your data loss prevention policy. Controls may include role-based access, encryption, masking financial data, etc.
• Set up DLP monitoring rules: Configure rules that detect potential hacker data breaches or policy violations in real-time. For example, set rules that see when users transmit healthcare data outside the network perimeter.
• Standardize data security tools and initiatives: Minimize complexity by standardizing DLP tools across the infrastructure per Gartner recommendations. Define standard data security protocols and configurations.

Prevent Data Loss with the ZenGRC Platform

As organizations generate and consume ever-increasing amounts of data, they often need help using it appropriately, storing, archiving, and destroying it. These days, manually managing the data lifecycle isn’t feasible. It is inefficient and resource-intensive, creating serious security and compliance risks.

The ZenGRC allows you to be more strategic with IT risk management by putting your business activities front and center. Discover a modern way to manage your risk posture with the ZenGRC Platform, allowing you to understand and act on your IT and cyber risks, all in a single unified platform.

Using AI, the relationships between assets, controls, and risks are automatically created, alerting you to changes in your risk posture and making it simple to grow and manage your risk programs. With dashboards and reports that provide contextual insights, it’s easier to communicate with key stakeholders and make informed business decisions with the ZenGRC platform.

Become more strategic with your IT risk management. Talk to an expert today to learn more about how the Reciprocity Product Suite can help your organization manage risks and compliance.