What Is Data Loss Prevention (DLP)? [Complete Definition]

With big data serving as the primary paradigm for modern business, data loss prevention has become a critical concern for data scientists and security experts. 

What is data loss prevention? It is the collection of technologies and policies used to prevent the theft, corruption, or unauthorized disclosure of sensitive information outside the boundaries of an organization’s IT infrastructure.

What Is “Data Loss”?

Data loss is the damage, destruction, or disclosure of information such that it is rendered unreadable, unusable, or no longer suited for its intended purpose.

This definition addresses some of the complications of data loss. For the most part, data is hard to “lose” simply because copies are easy to make, and if necessary, we can recover data from computers with the right tools. 

However, data can be “lost” because it is displayed or removed to an outside location, viewed by unauthorized people, or corrupted. Some of the most common forms of data loss include:

• External Threats (Extrusion): The most straightforward form of data loss is when an outside party attempts to take control of data and move it outside a company’s systems. For example, when a hacker steals a dump from a corporate database, the local copy of the database may remain on the company’s servers even though the hackers have created their copy externally. This is still considered data loss.
• Internal Threats: Likewise, if an individual “on the inside” of a company works with an outsider to steal information, they will almost always leave with a copy of the data without destroying it. This form of espionage is considered data loss. 
• Accidental Disclosure: Sometimes, accidents happen. An employee accidentally attaches a sensitive file to an email or walks away with a work laptop. Even though these are accidents, they are still considered effective forms of data loss that can cause significant headaches regarding security and compliance when allowed to build up over time.
• Alteration or Destruction: Contrary to popular belief, data is not eternal. Hardware failure is common, as are failures that come from incorrect automation or misconfigured software. In major cloud systems without DLP measures in place, it’s relatively easy for data to be corrupted, altered, or destroyed simply as part of everyday operations. 

Data loss prevention is the series of technologies, practices, and policies geared to prevent data loss due to accidental loss, loss of integrity, or malicious attack. Specifically, these DLP systems will impact data infrastructure that contains sensitive or mission-critical data. In this context, sensitive data includes:

• Personally Identifiable Information (PII): Any information that can be used to identify a user outside the system. PII may include phone numbers, Social Security numbers, address information, family information, etc.
• Protected Health Information (PHI): Any information related to the provision of healthcare, mental care, or the payment for care services with a provider or business associate. 
• Federal Tax Information (FTI): Any information, including PII, tied to specific tax transcripts, records, or filings. 
• Controlled Unclassified Data (CUI): Any information generated by contractors working within the Department of Defense (DoD) supply chain in partnership with defense agencies. This information isn’t classified as a military secret but still represents sensitive government information. To protect CUI, suppliers that conduct business with the DoD must comply with Level 2 practice requirements in Cybersecurity Maturity Model Certification (CMMC) 2.0. 
• Intellectual Property (IP): The intangible property of an individual or organization, including patents, trademarks, and trade secrets.

What Are the Components of a Data Loss Prevention Strategy?

The necessity of data loss prevention has become readily apparent in the world of massive, cloud-based Big Data infrastructure. With terabytes of data being transmitted, processed, or stored at any given time, the opportunities for potential data loss exponentially increase.

Then, businesses and other organizations must have broad DLP strategies in place to handle loss prevention. These strategies should be part of a data loss prevention plan, typically a more significant data governance plan. Data-sharing within digital businesses creates risk—both security and compliance related. 

Some of the components of this strategy include:

• Securing Data at Rest, in Motion, and in Use: At-rest and in-transit encryption are necessary for proper data prevention approaches. Encryption for information in a database or moving through networked systems is an already-common practice. Still, many companies must also take steps to secure data protection while it is used through hardware encryption or other methods. 
• Securing Endpoint Devices: Some of the most common forms of data breach occur when an endpoint device (a laptop or smart device with access to a secure IT system) is left unattended. At a minimum, organizations should secure these devices with multi-factor authentication (ideally including biometrics) and encrypted hard drives. 
• Integrity Controls: Integrity maintains data alterations and interactions records to avoid data loss. These tools can include input logging, event and transaction logging, file event logs, and file versioning and recovery. 
• Intrusion Detection and Intrusion Protection Systems: Intrusion detection systems (IDS) and intrusion prevention systems (IPS) allow security managers and administrators to identify any attempt to enter a system to steal files. On a larger scale, security information and event management (SIEM) can include intrusion detection and prevention on a more comprehensive scale.

What Are Some Best Practices for Effective Data Loss Prevention?

The best practices for DLP are, in many cases, leveraging the right technology to cover potential external and internal threats while monitoring systems for integrity. For larger organizations, however, this can get sufficiently complex to make the process seem untenable. 

It’s important to look at the big picture of your organization’s data infrastructure with some of these practices:

• Implementing Organizational Loss Prevention Policies: Implementing a data loss prevention policy is a non-negotiable part of this process. It may be integrated into a more extensive data governance or security plan. Still, it should clearly define the sensitive data your systems hold, where that data moves and who interacts with it, and the necessary controls to ensure its integrity and security. 
• Integrating the Role of Chief Information Security Officer (CISO): Traditionally, the role of the Chief Technical Officer (CTO) or Chief Information Officer (CIO) would handle data security and integrity.
  
  But, because big data has become so complex yet necessary for the modern enterprise, the office of CISO emerged. CISOs in these dedicated roles can help your organization have a clear eye on deploying policies and practices throughout the enterprise.
• Clearly Defined Authentication and Access Controls: A vital part of data loss prevention is to ensure that only authorized individuals view that data. As such, authentication and authorization are critical components that should be integrated seamlessly throughout an organization, ideally through a centralized platform or single sign-on (SSO) solution.
• Using SIEM or Other Event Monitoring Tools: SIEM tools are indispensable for monitoring file activity. With a fully implemented SIEM solution, you can look at intrusion detection and prevention with an understanding of your entire data management context. 

Comprehensive Security and Data Loss Prevention With Kiteworks

When it comes to governing and securing sensitive content when it is exchanged between individuals and organizations, DLP needs to be integrated for both inbound and outbound communications. For outgoing communications, DLP identifies PII, PHI, IP, and other sensitive information. Using content-policy zero trust in the Kiteworks Private Content Network, organizations can block files from being sent via email or shared or transferred via file sharing and managed file transfer (MFT). Notifications to security personnel can be sent in real time through logged metadata captured in syslogs that feed into SIEM systems in the SOC. 

Consolidated DLP data can be generated in reports to satisfy regulatory compliance. In addition to data privacy regulations such as the Health Insurance Portability and Accountability Act (HIPAA), General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Personal Information Protection and Electronic Documents Act (PIPEDA), and others, DLP-generated data reports serve other areas of regulatory compliance such as CMMC, FISMA (Federal Information Security Management Act), GLBA (Gramm-Leach-Bliley Act), and others. 

For more information on the Kiteworks Private Content Network and how DLP is integrated into its content-policy zero-trust capabilities, schedule a custom-tailored demo today.

Additional Resources

• Report Get 15 Predictions for Managing Your Private Content Exposure Risk in 2023
• Guide Map CMMC 2.0 Requirements to Your Sensitive Content Communications
• Report Benchmark Your Security and Compliance Risk for Sensitive Content Communications

*** This is a Security Bloggers Network syndicated blog from Cyber Security on Security Boulevard Archives - Kiteworks authored by Robert Dougherty. Read the original post at: https://www.kiteworks.com/secure-file-transfer/data-loss-prevention/