Role of DLP in Protecting Financial and Healthcare Data

Data is the most important component of an industry, particularly for the financial and healthcare industries. These industries process vast amounts of highly sensitive information, including financial records, transaction histories, patient health records, and treatment plans. It’s essential to address this issue as soon as possible, as the confidentiality, integrity, and availability of this information are crucial for operational efficacy and compliance. However, they also play a vital role in maintaining the trust of the general public and respecting individual privacy.

Considering the advancements of cyber threats, as well as the prospect of risks from the inside (unintentional due to an insider threat or by accident), reasonable security options are more important than ever! Many organizations find that one of the most valuable security options for protection against a data breach is Data Loss Prevention (DLP) software. Most DLP solutions apply holistically to address the need to discover, monitor, and protect sensitive data from leaving the organization’s perimeter. Financial and healthcare-related data are consistently among the most critical data assets to protect. Therefore, DLP solutions are essential to employ in relation to protecting this data.

In addition, implementing cybersecurity best practices, such as data classification, phased DLP deployment, and contextual policy enforcement, is critical to ensuring effective data protection across financial and healthcare environments.

Why is protecting financial and healthcare data important?

The risks of a data breach in the financial or healthcare sectors can be devastating:

Financial Sector:

• Financial Loss: Money can be quickly stolen via various types of fraud, and remediation and recovery costs can add up quickly.
• Reputational Loss: Trust can be lost, resulting in lost business and long-term damage to the brand.
• Legal Liabilities: The Possibility of lawsuits from affected customers.

Healthcare sector:

• Privacy Breaches: Inadvertently revealing potentially harmful and upsetting sensitive patient health information (PHI).
• Reputational Damage: Breach patient trust and damage the credibility of any providers in your organization.
• Regulatory Penalties: There are increasingly strict data protection regulations (e.g., HIPAA in the US) that require special protection of data and impose serious penalties for violations.
• Legal Liabilities: Risk of lawsuits from patients whose privacy they violate.

DLP:

DLP software is designed on the premise of knowing what sensitive data an organization has, where it’s stored, and how it’s used; it puts in place policies to restrict, stop, or prevent activities involving the access, use, and transmission of sensitive data.

Here are some ways DLP software is critical to the protection of financial and healthcare data:

Data Discovery & Classification: Identifying the Crown Jewels (i.e., sensitive data, PII, PHI, etc.)

As mentioned above, the first and foremost thing to address in any sensitive data protection strategy is what sensitive data you have, where it is, and what type of data it is. DLP solutions use sophisticated data discovery technologies to look into data stored on endpoints, in network storage, cloud storage, in databases, and in applications, to find financial records (e.g., account numbers, transactions, card numbers) and healthcare data (e.g., patient names, medical history, diagnosis codes, insurance information).

Data discovery is only half the equation; once we discover sensitive data, we want to classify it using a data classification process. This Phase can include more defined rules, keyword searches, pattern matching (e.g., format matching of card numbers or national identification numbers), or even machine learning. Only once we classify the data can the organization implement security controls based on the level of risk posed by the various data types and their classifications. For example, we can appreciate that a patient’s diagnosis is a highly sensitive piece of healthcare data and will deploy risk-based controls far above those used for a general appointment reminder.

2. Monitoring Data in Motion, at Rest, and in Use – Visibility

DLP offers an ongoing view of how sensitive financial and healthcare data progresses through the organization.

Data in Motion: DLP analyzes your network traffic, email communications, file transfer activity, and data shared via messaging to identify when sensitive information is being shared outside of your organization’s specifications or in unauthorized instances. For example, DLP can discover and block a user’s unauthorized attempt to email PHI to their personal email account or upload financial reports to a publicly available file-sharing website.

Data at Rest: DLP scans your stored data on multiple systems to ensure it is secured. Examples include determining whether sensitive data is encrypted, identifying sensitive data stored in unauthorized locations, or detecting sensitive data that appears to have overly permissive access rights. For instance, DLP may flag instances where unencrypted patient health data is stored on an employee’s local hard drive.

Data in Use: DLP monitors user actions occurring at endpoints, such as accessing, copying, printing, or editing sensitive files. It is designed to prevent illicit actions by users, such as copying a list of customer credit card numbers to a USB drive or printing a complete patient medical history without authorization.

This level of monitoring can provide organizations with valuable information about the access and use of sensitive data, enabling them to mitigate risk before issues arise.

3. Policy Compliance: Secure Your Data.

DLP software enables organizations to create and apply fine-grained security policies that define how sensitive financial and healthcare data is handled. Policies can logically represent data types, user roles, and applications. For example:

• Blocking the email transmission of unencrypted financial data.
• Prohibiting copying patient health records to removable media.
• Limiting access to financial databases to certain individuals.
• Watermarking sensitive documents.

When a user takes an action against a DLP policy, the DLP software can take a number of actions, such as blocking the action, notifying administrators of the violation, encrypting the data, or warning the user. This level of policy enforcement is essential if you want to reduce the impact of accidental and intentional data leakage.

4. Contextual awareness: Understanding “why” users are taking actions with data.

Advanced DLP solutions evaluate multiple aspects surrounding data access and usage, including the user, device, application, time, and destination. By determining that context, DLP makes smarter decisions about breaking a rule, allowing the action, or monitoring it. For example, when a treating physician accesses a patient’s record during their shift, it is acceptable; however, if a non-medical staff member accesses the record after their shift, an alert will be generated. Furthermore, if an authorized user exports a financial report to an authorized internal server, it would be authorized. However, if that same user exports the same report on an external website, it would be blocked.

5. Incident responses and remediation: Taking action quickly when things go wrong.

No matter how effective a preventive solution or control is, incidents related to data security will still occur. When it comes to incident response, DLP software is a crucial component of the puzzle. DLP software standardizes alerts and gives the user a comprehensive log of policy violations or potential data loss events. This allows security teams to quickly identify, investigate, and contain incidents in a timely manner. In most instances, they are dealing with incidents that could be very costly to the organization, especially with sensitive financial or health-related information.

The audit trails created by the DLP tool can be a significant asset for forensics, as the organization can review the breach, identify its root cause, and assess the extent of data accessed, along with remediation actions and measures to prevent a similar event in the future.

Adapting DLP in Finance and Healthcare

Generally, the principles of DLP are the same, though the implementation must be adaptable to the regulations and data types associated with the financial and healthcare sectors.

Financial Institutions: DLP must be set up in conjunction with guidelines such as PCI DSS, which protects cardholder data and restricts customer financial information. Therefore, DLP policies establish controls to prevent the leakage of credit card numbers, bank account numbers, and non-publicly available financial information.

Healthcare Organizations: DLP implementations must address compliance with laws such as HIPAA to protect Protected Health Information (PHI). Policies would prevent the naming of the patient, along with any unique identifiers, medical history, diagnosis, and treatments. This is no longer to be viewed in the same light as it was historically.

Conclusion: DLP as the Basis for Data Protection

In the wake of heightened threats and stringent regulations, Data Loss Prevention (DLP) software has become indispensable for organizations that handle sensitive financial and healthcare data. Moreover, DLP provides visibility and policy enforcement of unauthorized data movement, which can be an additional layer of security to protect valuable information, maintain compliance, protect trust, and protect individuals from the impact of a breach. As a strategic component of an information security management program, developing a DLP strategy is not just a technology approach, but a key leadership initiative.