Data Loss Prevention (DLP) is a critical tool to help organizations mitigate the risk of malicious or accidental data leaks. This piece emphasizes the importance of understanding DLP business drivers, the evolving technology landscape and the processes behind these tools to maximize their value. This piece also delves into new areas, such as DLP’s role in the context of generative AI and the remote workforce.
Planning a DLP Deployment
Successful DLP programs start with planning. DLP products introduce some friction for business users, so your strategy should include engaging stakeholders right from the beginning to ensure everyone understands and supports the objectives of the program and expectations are set appropriately—especially, with senior executives and business leaders. While there are many considerations when preparing for a DLP deployment, it is important not to overlook some key areas:
- Why are you deploying DLP? The primary driver for DLP is protecting critical business data, but other drivers may include compliance (e.g., with the EU’s GDPR), audit and regulatory pressures, user education (e.g., to encourage usage of an encrypted email gateway) and uncovering insider threats. Currently, there is no explicit mandate for DLP within any cybersecurity regulations. Instead, regulations focus on a broader goal of data protection and privacy, indirectly suggesting solutions like DLP as best practices. Of course, this could change in the future.
- What data are you protecting? Many deployments start with obvious business problems, like protecting cleartext credit card numbers and Social Security numbers (SSNs). However, DLP’s real business value comes from looking at much harder-to-define data, such as M&A data or other intellectual property. These data types are much more difficult to capture in a DLP rule without having direct involvement from business representatives.
- What communications channels are in scope? A good rule of thumb is if you are looking to protect compliance-related material (e.g., credit card numbers or SSNs) from leaving the firm, then network or email-based DLP might be sufficient for your needs. More complex requirements, such as looking for insider threats, will likely require a DLP endpoint solution with an agent installed on every desktop. Many companies use a combination of both network and endpoint DLP, and many DLP products handle multiple channels.
- How will you handle encrypted traffic? A good portion of your network traffic might be encrypted. Estimates indicate nearly 80% of network traffic is encrypted. Methods for forwarding encrypted traffic via proxies, application delivery controllers or dedicated SSL decryption solutions should be a consideration for your DLP appliances. Otherwise, you’ll likely need to focus on endpoint solutions.
- How will you manage DLP in the context of AI and chatbots? As AI and chatbots become more prevalent in business operations, it's crucial to consider how DLP can be applied to these technologies. This includes understanding the limitations of DLP in this context and developing strategies to mitigate potential risks. While DLP can help secure data, it may not fully control the output of generative AI models. Therefore, organizations need to develop separate strategies to mitigate potential AI risks, such as inappropriate data generation or misuse of sensitive information.
- Remote workers: With the shift toward remote work, organizations face new challenges in securing data outside of traditional office environments. It's essential to choose a DLP solution that offers extensive protection for data accessed on personal devices and unsecured networks. Many DLP solutions provide tools to help secure collaboration in Teams, Slack and other enterprise messaging tools, ensuring data shared among remote team members remains protected, regardless of where machines are physically located.
Download: Data Protection and Classification Policy Template
Developing a DLP Response Strategy and Process
DLP tools generate a multitude of alerts that require attention, so it's important to plan your response strategy well in advance of deploying software. Many organizations assume the security team will handle all DLP events. However, an email event triggered by a rule looking for credit card numbers might indicate data theft just as easily as it might be a legitimate business transaction over an insecure communications channel. Engaging privacy, compliance or even employee managers is a best practice for distinguishing between poor business practices and malicious intent. We also recommend exploring automated software-based response options wherever possible. Most DLP tools can either block, force encryption, alert or quarantine sensitive data. Consider which scenarios will require human intervention and which could be automated. For instance, repeated attempts to transmit sensitive data could trigger an automatic block, while a single instance might just warrant an alert.
In the era of remote work, it's also essential to consider how your DLP strategy will apply to employees working outside the traditional office environment. This might involve requiring additional training or specific guidelines for remote workers to ensure they understand and adhere to all data protection policies.
DLP Industry Trends
DLP technology is evolving along with the threat landscape. By integrating cutting-edge advancements, these solutions are evolving to help protect sensitive data more effectively than ever. Here are some of the most notable trends:
- Integration of AI and machine learning (ML): Not surprisingly, AI and ML are increasingly being integrated into DLP. AI and ML technologies enhance the ability of these tools to identify and even classify sensitive data, as well as detect anomalous behavior. They can also help automate policies, reduce false positives and automate workflows for resource constrained security teams.
- False positive reduction: The integration of advanced technologies, including exact data matching and document fingerprinting, has significantly improved the precision of DLP solutions. Exact data matching allows for the identification of specific data elements across various formats and locations, reducing the chances of misidentification. Document fingerprinting enables DLP solutions to recognize the unique “fingerprint” of a document, thereby identifying sensitive documents, even when they have been modified or reformatted.
- Evolving role of DLP in privacy compliance: With increasing regulations pertaining to data privacy, such as the GDPR and California Consumer Privacy Act, DLP solutions are evolving to place a stronger emphasis on data minimization, anonymization, encryption and deletion to comply with these stringent laws.
- DLP as a service (DLPaaS): DLPaaS addresses the need for advanced DLP solutions without heavy infrastructure investment. This subscription-based or pay-per-use model allows businesses to adapt and scale their DLP solutions according to their evolving needs.
- DLP solutions for remote work and collaboration: The rise of remote work has necessitated the refinement of DLP solutions. These solutions now focus on supporting secure and compliant collaboration, enabling data sharing and communication, while preventing unauthorized access, leakage or misuse of sensitive information.
- Adoption of a zero trust model: The zero trust model, which verifies and secures every access request, data transaction and network connection, is gaining traction in the DLP space. This approach is particularly crucial in remote work scenarios, where data is often accessed from outside the traditional organizational perimeter.
These trends collectively signify the evolution of DLP technologies, paving the way for a future where data leakage prevention is seamlessly integrated into the ever-changing and multifaceted digital landscape.
DOWNLOAD: Zero Trust: A Step-by-Step Guide
Engage Stakeholders and Start Small
We recommend taking a phased approach with DLP deployments. Start with some simple objectives to prove the tools and the processes. For example, create an alert that triggers once a certain threshold of instances of credit card data in North America is reached or select a single business unit to monitor. The objective is to make sure whoever is responding to DLP alerts can handle the event volume and there are not too many false positives. You can also put most DLP solutions into a “monitor only” mode so you can see the potential impact a rule will have when it’s turned into blocking mode.
DLP Pitfalls to Watch Out For:
Ignoring the human factor: It’s important to strike a balance between security and usability. Overly restrictive DLP policies can lead to employee frustration, reduced productivity and even attempts to bypass security measures, which can increase the risk of data exposure. DLP education and training should be designed so employees understand the importance of data protection and are equipped with the knowledge to handle data responsibly.Not enabling “free” DLP controls first: Companies looking to get started with a general data protection program can start by making sure basic security controls are already in place. For example, disabling USB storage can generally be accomplished through AD group policy and doesn’t require special software to be deployed. Ensuring least privilege access controls, encrypting hard drives and implementing network segmentation can also reduce the risk of data loss without deploying a formal DLP product. Many DLP products, such as Microsoft and Forcepoint, include some basic data discovery capabilities. Take the time to lock down data before putting leakage controls in place.Not engaging all stakeholders: We recommend creating a DLP steering committee that includes business representatives, as well as stakeholders from legal, privacy, compliance and human resources (HR), at a minimum. This will ensure everyone is on the same page with what events are being triggered and the response.Big bang deployments: Use a phased approach for enterprise DLP deployments. The more focused the initial deployment is, the more likely it is to be successful. Start small and grow from there.Not fine-tuning the DLP system: Generating too many alerts will overwhelm responders and raise audit and regulatory issues if alerts are ignored. DLP systems generally require tuning to reduce false positives. This is an iterative process, so plan to revisit and adjust alert quality frequently.Overemphasis on compliance: While compliance with regulations is important, it should not be the only focus. DLP should also aim to protect business-critical data and intellectual property, even if they are not covered by any regulations.
DPL Adoption: How to Add Business Value
DLP programs take some time to add real value beyond basic blocking of obviously sensitive data like credit cards. Put some time into understanding business requirements and your event response processes. This will help ensure you’re getting the most value out of your investment. Remember:
- Be clear why you’re deploying DLP in the first place: Understanding your business drivers and the complexity of your needs will help drive the right product or solution for your organization. The best DLP deployments detect not only compliance-driven data, but also data that has business value.
- Engage stakeholders early: If you plan on disciplining employees who mishandle confidential information, make sure your process is vetted well beyond the security group. HR, legal and potentially physical security should all be aware of your DLP program if your events could result in employee termination.
- Don’t go it alone: The biggest challenges with DLP deployments happen when the security group works in isolation and then tries to respond to every event alone, without any business context or input. Engage your business stakeholders and have them help guide your program.
Finally, DLP as a managed service, offered by providers like Digital Guardian and others, could also be an attractive option for resource-constrained organizations. These services can provide expert guidance and support, helping to ensure your DLP strategy is effective and efficient. When it comes to DLP deployments, start small, engage stakeholders and plan your processes in detail. Don’t just focus on the products.
Although reasonable efforts will be made to ensure the completeness and accuracy of the information contained in our blog posts, no liability can be accepted by IANS or our Faculty members for the results of any actions taken by individuals or firms in connection with such information, opinions, or advice.