Most organizations have at least one thing in common: every year, they’re generating and consuming more and more data. Dealing with all this data can be overwhelming, and especially so for those organizations that haven’t fully embraced the digital transformation and the cultural shifts that come along with it.
As your data grows, so too 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 serious cybersecurity threats faced by organizations around the world-and it’s likely that the number and frequency of these events will only continue to soar in the coming years.
If your organization hasn’t already, the time to implement a data risk management program is now. 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 cybersecurity threats, both internally and externally.
One of the most important components of a successful data risk management program is data loss prevention (DLP), a set of tools and processes used to ensure that your organization’s sensitive data isn’t lost, misused, or accessed by unauthorized parties.
Sometimes also called data leakage prevention, a DLP strategy should ultimately aim to incorporate both technology and programmatic elements with a holistic approach that prevents data loss throughout your organization and all the places its data resides.
In this article, we’ll take a closer look at data loss prevention, discuss why it’s important, and introduce some of the best practices when it comes to creating a DLP strategy and a DLP policy that protects your organization’s most sensitive data from cybersecurity threats.
What is Data Loss Prevention?
Almost every organization creates, transmits, and stores some form of sensitive data. Sensitive data is information that must be protected against unauthorized access in order to safeguard the privacy or security of an individual or organization. This data might take the form of 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 consist of more sensitive information such as social security numbers and driver’s license numbers-data you definitely wouldn’t want on the dark web. PII can belong to your employees, customers, or stakeholders, and in some cases, it’s even protected by law.
For example, the European Union’s General Data Protection Regulation (GDPR) protects the personal information of consumers who live 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, are meant to protect consumers from having their data unintentionally leaked or lost due to a malicious actor, insider threat, or unknowing employee. When an organization does fall victim to a data leak or data breach, it usually results in significant financial loss and reputational damage in addition to any regulatory and legal consequences.
In fact, the average cost of a data breach was $4.2 million in 2021. While most of that money usually goes toward repairing reputational damages and loss of business, a lot of it also goes toward paying the hefty non-compliance fines that are 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 affected by data breaches resulting from organizations’ poor or nonexistent data loss prevention strategies, their expectations about data privacy will only continue to get higher. Organizations that want to stay relevant will need to prioritize DLP and transparency if they want to stay in business.
While most cybersecurity strategies that are aimed at preventing data breaches focus on addressing external security threats like malware and phishing attacks with firewalls and antivirus software, data loss prevention strategies are centered around addressing internal threats such as a disgruntled or negligent employee. Many organizations simply don’t realize-or don’t want to acknowledge-that these types of insider threats can pose serious risk 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 that will help you detect potential data breaches and prevent them 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 in order 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): this includes data that transits or leaves the network to the internet, including emails.
- Cloud DLP: this includes data residing on the cloud or in personal email providers.
Which types of DLP you choose to prioritize will ultimately depend on the specific needs of your organization, and should inform any decisions you make regarding which DLP solutions you select to automate parts of the process.
Ideally, your DLP strategy should integrate DLP tools including DLP software with a holistic program that’s aimed at protecting your data from internal threats throughout your organization. This means you’ll not only need to create a DLP policy that’s tailored to your business needs, but you’ll also have to address the added challenge of selecting the best DLP solution to help you implement and maintain your data loss prevention program.
When it comes to DLP software, the core components really haven’t changed much in the last few years, with the exception of cloud computing. Most DLP solutions are designed to discover and analyze both the content and the context of your organization’s data in order to determine if it matches a pattern or expression. Once a pattern is matched, 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, but most 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 something called 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 that are used to identify individual people. Fingerprinting is especially useful for organizations that need to 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 you can avoid them.
Most Common Data Loss Prevention Mistakes
When it comes to DLP, there’s a lot that 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 face 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 that they rarely ever make it to the blocking phase. This is because there is often too much focus on fine tuning DLP policies and procedures to eliminate false positives, and not enough actual blocking going on. Organizations that do implement DLP can spend months or even years working to ensure that their DLP program only generates information of value.
Today, most organizations are generating insurmountable amounts of sensitive information, which means that you’ll need to decide which data to protect. Cast too wide of a net, and you’re likely to end up with more false positives. But cast too narrow of a net, and you’ll only be able to address one specific area of the business, leading to a lot of missed content.
Organizations with a DLP strategy need to understand that DLP is not a sure fire way to stop data loss. 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. It’s likely that there will be a noticeable decrease in threatening internal activity simply because people know that you’re watching.
Now that you have a better understanding of DLP, why it’s important, 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 it comes to 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 the specific needs of your organization. However, there are some data loss prevention best practices that 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 make sure that you have the right people in place to put the technology in place and to 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. For each party, clearly define their role and responsibilities involved 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.
If internal resources aren’t available to support DLP operations, you should consider partnering with a managed service provider that specializes in DLP.
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 that you need to protect at all costs.
Then, you need to define your metrics. DLP is a great system to show how much data is getting flagged and where the biggest 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 important 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 amounts of 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
To identify some of the parameters we outline above, you’ll need to start with data identification and classification. 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 helps organizations control user data access and avoid storing sensitive data in unsecure locations, which can reduce the risk of data leaks and data loss.
Your most critical or sensitive data should be clearly labeled with a digital signature that denotes its classification. As data is created, modified, stored or transmitted, these classifications will need to be updated.
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).
For critical business data at rest or in transit, you should also consider using data encryption to keep your data safe. Securing all the places where sensitive data could reside, even temporarily, will help prevent data breaches or data leaks even without a DLP policy. Finally, it needs to be said that your organization should avoid saving unnecessary data at all costs.
A rigorous patch management strategy is also an essential part of data protection and cybersecurity. Patch management will help your organization to ensure that all your operating systems and applications in your IT environment are up to date. 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 too restrictive, and too loose.
For example, if part of your business process involves one employee sending sensitive information to another employee, you’ll need to make sure that there are actually 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 the technology you’ll use, will meet your compliance needs and observe the deficiencies in your triage process.
Educate End Users
As mentioned above, simply letting your employees know that you’re watching is often enough to deter any 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 important and what’s at stake.
More often than not, data loss is a result of simple end user mistakes, ie. sending credit card info via email, or losing a USB storage device containing sensitive information. In these cases, end users often don’t know that they’re doing anything wrong. Sometimes, internal threats are made up of malicious actors, but DLP is likely to deter many of those types of actions. The more protections you have in place, the less likely that you will be targeted to begin with.
Your educational program should also take into account whether you want to punish bad behavior with punitive actions, or reward good behavior with an incentive program. There are benefits and drawbacks to each, but these types of programs are often successful in reducing the amount of security incidents, and phishing attacks in particular.
Another important part of your educational program will be to educate your executive and senior leadership so you can shift the culture toward a more DLP centric approach.
Shift the Culture
As with most programs, a successful DLP strategy will necessitate a cultural shift. It’s likely that you’re going to require end users to take different actions than they’re used to, which means there will most definitely be a learning curve. It can be difficult to teach an old dog new tricks, and this 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’re going to make serious changes to business processes as a result of DLP, you also need to provide your employees with solutions to replace those processes that are no longer considered secure.
Monitor and Repeat
As part of your DLP program, you’ll need to 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
The cost of 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 then start to look 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 are using 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.
Prevent Data Loss with the Reciprocity ROAR Platform
As organizations generate and consume ever-increasing amounts of data, they often struggle to appropriately use, store, archive, and destroy it. These days, manually managing the data lifecycle simply isn’t feasible-it’s inefficient, resource intensive, and it can create serious security and compliance risks.
The Reciprocity® ROAR Platform, which underpins Reciprocity ZenRisk and Reciprocity ZenComply, gives you the power 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 Reciprocity ROAR Platform, giving you the ability to understand and act on your IT and cyber risks, all in a single unified platform.
With an incredibly intuitive user experience paired with in-application expert guidance, you can assess, manage, and communicate risks and their potential business impact. 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 Reciprocity ROAR platform.
Become more strategic with your IT risk management and talk to an expert today to learn more about how the Reciprocity Product Suite can help your organization confidently manage risks and compliance.