A data loss prevention (DLP) strategy is a plan that organizations implement to detect and prevent the unauthorized access and exfiltration of sensitive information. The goal of a DLP strategy is to minimize the risk of confidential data leaks that could put an organization at risk of data breaches, non-compliance penalties, intellectual property theft, and reputation damage.
Why is a DLP strategy important?
With the exponential growth of data, digital transformation initiatives, and more employees working remotely, organizations are generating and storing more sensitive data than ever before across disparate systems and locations. This data proliferation makes it extremely difficult to maintain consistent security controls and practices. Without a proactive strategy, sensitive data can easily fall into the wrong hands either from malicious attacks or accidental data leaks by employees.
Some key reasons why a strong DLP strategy is critical include:
- Protecting intellectual property and trade secrets
- Preventing reputation damage and loss of customer trust
- Avoiding data breach notification costs
- Reducing the risk of PCI and HIPAA non-compliance fines
- Minimizing insider threat incidents
Having a comprehensive DLP strategy greatly reduces the risks associated with confidential data loss and helps demonstrate diligence to auditors and regulators.
Key elements of a DLP strategy
An effective DLP strategy consists of people, processes and technology controls working together. Key elements include:
Data discovery and classification
The first critical step is identifying and classifying sensitive information repositories across the organization. This provides visibility into what data exists, where it’s located, who owns it, and its level of sensitivity. Data discovery using automated scanning tools is important for this process.
Policy definition
Organization-wide DLP policies should outline acceptable data use, sharing, encryption, retention and disposal practices based on data classification levels and regulatory requirements. Policies help establish data security standards for employees.
Risk assessment
A risk assessment evaluates potential data leak scenarios through various endpoints like email, web browsers, endpoint devices and networks. Identify highest risk users, systems and transmission methods.
Endpoint security controls
Deploy endpoint DLP software, data encryption and rights management solutions to monitor and control how sensitive data is stored, accessed and shared on PCs, laptops, mobile devices and removable media.
Network security controls
Install network DLP solutions to analyze inbound and outbound traffic for unauthorized data movement. This helps detect and block potential data exfiltration attempts at the network perimeter.
Cloud security controls
Implement cloud access security brokers and DLP tools for SaaS applications that employees use for collaboration, data storage and transfers. This protects cloud data.
Email security controls
Configure email DLP capabilities like deep content inspection and policy-driven encryption to protect confidential data shared via email.
SIEM monitoring
Aggregate and correlate DLP event logs using a SIEM solution. This provides visibility into policy violations, suspicious user activity and data leaks.
Incident response processes
Define processes for investigating DLP security events and responding to confirmed data leaks. This speeds containment and mitigation actions.
User training
Educate employees on DLP policies, proper data handling, and how to identify and report security incidents. This improves compliance.
Regular policy review
Update DLP policies frequently based on new systems, users, applications and threat intelligence. Perform periodic audits to maintain an effective strategy.
Key capabilities of DLP solutions
DLP tools offer advanced capabilities that enable organizations to implement data-centric security controls aligned with the DLP strategy. Here are some key features:
Data discovery and classification
Automatically scan structured and unstructured data repositories across endpoints, networks and the cloud to catalog sensitive information and assign classifications.
Policy definition
Provide pre-defined regulatory policies (PCI DSS, HIPAA, etc.) that users can customize with advanced content matching rules, contextual scans and fingerprinting.
Monitoring and blocking
Monitor real-time data access, movement and sharing activities for policy violations. Block identified breach attempts.
Incident workflow
Centralize incident response workflows to streamline investigation and remediation of DLP security events.
Reporting and analytics
Generate detailed reports on data discovery results, policy matches, user activity monitoring and security incidents for auditing needs.
Data masking
Dynamically mask sensitive data fields with pseudonymized information to allow transactions for non-production use cases.
Encryption
Encrypt sensitive content before it leaves user endpoints with file and rights management capabilities.
Key stakeholders for a DLP program
Developing and implementing an enterprise-wide DLP strategy requires engagement from stakeholders across departments. Key participants typically include:
- CISO and information security team – Establish the vision, strategy, policies, controls and processes for the DLP program. Provide guidance and oversight for implementation.
- Compliance team – Define regulatory policies for data protection based on requirements. Assess effectiveness of controls.
- Legal team – Ensure DLP policies and procedures comply with laws and regulations. Advise on response processes.
- Data/information owners – Classify and inventory sensitive information. Contribute to policy definition.
- IT team – Deploy and maintain DLP controls across endpoints, networks and cloud environments. Support integrations.
- Business unit leaders – Sponsor user training initiatives. Validate policies balance business needs.
- Human resources – Incorporate DLP responsibilities into employee agreements. Enforce disciplinary actions.
- Users – Complete required training. Report suspected data leaks. Follow defined policies.
Collaboration across these stakeholders is vital for establishing a successful cross-functional program with engagement across the organization.
Challenges of implementing a DLP strategy
While critical, implementing a DLP strategy can also pose some challenges that organizations need to overcome. Some common issues include:
Scoping and priorities
Determining the right scope, order of implementation and priorities across endpoints, networks and cloud can be difficult given the breadth of sensitive data.
Solution sprawl
Point solutions for email, web, endpoints and networks can cause data blindspots and complex integration requirements.
Policy definition
Establishing policies that meet both security and business objectives around data use can be a balancing act requiring agreement.
Scalability
DLP controls must keep pace with the scale and growth of regulated data across systems and locations.
Performance impacts
Encryption and deep content inspection can strain resources and impact user experience if not managed closely.
False positives
Overly strict content matching rules can flag benign activities leading to alert fatigue.
User acceptance
The visibility into user activities provided by DLP monitoring can cause pushback without proper change management.
Organizations can overcome these hurdles with a phased rollout approach, strong executive sponsorship, user education, and by selecting integrated DLP solutions that provide automation, machine learning and customizability at scale.
Best practices for a DLP strategy
Some proven best practices for an effective DLP strategy include:
- Obtain executive buy-in and present a business case for funding
- Start with early wins by focusing on highest risk data first
- Select a centralized DLP platform over point solutions
- Leverage machine learning to maximize automation for classification and policies
- Involve stakeholders from legal, HR and business units
- Train users on policies and make them partners in the process
- Start with monitoring versus blocking to minimize business disruption
- Tune content matching rules to reduce false positives
- Review policies and refine regularly based on learnings
- Tie DLP controls into incident response processes
- Use reporting to demonstrate value and compliance to leadership
Conclusion
Developing a comprehensive data loss prevention strategy is a critical security initiative given rising data volumes and risk exposure. A successful DLP program requires involvement across the organization to align on policies, controls and processes that balance mitigating data leak risks with enabling business activities. Companies willing to make the investment in people, technology and governance can gain significant protection against regulatory non-compliance, reputation damage and loss of intellectual property resulting from confidential data falling into the wrong hands.