Data Loss Prevention vs. Data Leak Prevention: What You Need to Know?


By Prasanna Peshkar

In the age of digital operations, data is the heart of any business venture. Thus, shielding it from any harm is a critical necessity. Data Loss Prevention (DLP) and Data Leak Prevention (DLeakP) are two widely employed protective measures. Despite the frequent confusion between these terms, they denote separate strategies. In this article, we delve into the nuances of DLP and DLeakP, their best practices, and the pivotal role they play in robust cybersecurity.

What is Data Loss Prevention (DLP)?

DLP constitutes a method of ensuring the safety of corporate data from potential loss or intentional compromise. DLP assists businesses to stay compliant with privacy regulations applicable to their data, thereby offering complete data visibility. This technique can be employed across all segments of a company’s digital framework, encompassing endpoint, network, and cloud systems. As data resides in varied stages within these environments, the tools and solutions necessary for securing sensitive data will vary, depending on the corresponding environment.

There are diverse forms of data loss prevention, like endpoint DLP and network DLP, that serve the purpose of averting data loss within a company. The former concentrates on the safety of data on individual devices, while the latter focuses on preventing data loss during data transfer across the network.

What is Data Leak Prevention (DLP)?

Controlling data flow both inside and outside of an organization is the main focus of DLeakP. Data flow diagrams, digital rights management programs, and Zero Trust Network Access (ZTNA) are frequently combined to execute leak prevention effectively. The main goal of DLeakP is to prevent data transfers from the organization to unauthorized parties. Its main focus is on preventing unauthorized parties from receiving or accessing an organization’s sensitive and important data. For instance, “For many organizations, monitoring end-user access to sensitive information, as well as the movement of this data is an essential part of their cybersecurity program. Before the ubiquity of cloud platforms and hybrid work, this was done with an on-premises data loss prevention tool.”

The distinction between Data Loss Prevention and Data Leak Prevention

While data loss prevention emphasizes safeguarding data from active threats that could potentially damage or obliterate it, data leak prevention is more concerned with controlling data flow within and beyond an organization’s boundaries. DLP uses methods to avert data loss during regular usage, whereas DLeakP uses methods to prevent an unauthorized external data transmission.

What are the common causes of data loss and data leaks?

Data loss and data leaks can cause devastating effects on businesses, potentially leading to lasting damage. Data loss refers to incidents where data is accidentally removed or becomes corrupted, whereas data leaks pertain to scenarios where information becomes accessible to unauthorized individuals due to internal blunders. Here are the prevalent triggers for data loss and data leaks:

Frequent Triggers for Data Loss

  • Hardware Malfunction: Hardware breakdowns are the principal culprits behind data loss, where hard drive crashes or system failure account for about 67 percent of such incidents.
  • Human Mistakes: These comprise unintentional deletion, format blunders, and other user errors.
  • Malware and Viruses: These can manipulate or erase data, rendering it indecipherable for humans and software alike.
  • Device Theft or Loss: This may result in the loss of data stored on the lost or stolen device.
  • Power Interruptions: Power cuts can lead to data corruption or loss, especially if the computer does not undergo a proper shutdown process.
  • Natural Calamities: Catastrophes such as floods, fires, and other natural disasters can harm hardware, leading to data loss.
  • Software Corruption: Software can become corrupt due to bugs, glitches, or incompatibility issues.

Frequent Triggers for Data Leaks

  • Weak or Stolen Credentials: Cybercriminals often exploit stolen or weak passwords to access sensitive data, making this the most frequent cause of data breaches.
  • Social Engineering: This tactic manipulates individuals into surrendering their personal information, typically through phishing scams.
  • Poorly Configured Software Settings: If software settings are not configured properly, they can lead to unauthorized data access due to inadequate data security and sanitization.
  • Internal Threats: Employees may inadvertently or intentionally expose sensitive data.
  • Physical Intrusions: These involve direct physical access to devices or networks to pilfer data.

Effective Measures for Data Loss Prevention (DLP)

Here are a few effective measures for DLP:

  • Rank Your Data: Every business needs a DLP strategy to prevent unauthorized access or accidental deletion. The strategy should be centered around protecting valuable, sensitive, or regulated data.
  • Classify Your Data: Identifying the data that needs protection is the first step in creating a DLP policy. Once determined, access to this data and its storage locations should be evaluated, followed by rules set up for data protection.
  • Determine Risky Data Situations: A sound DLP program must understand data mobility and moments when it could be at risk. Understanding data usage and identifying risky behavior is crucial to formulate appropriate policies.
  • Track Data Movements: Monitoring provides metrics about risk-prone data. Effective DLP should understand why this is occurring and create controls for risk reduction.
  • Encourage Security Awareness: One of the best strategies to stop data loss is to regularly train personnel on security awareness. Employees should receive training on how to spot and report questionable activity.

Effective Measures for Data Leak Prevention (DLeakP)

Here are a few effective measures for DLeakP:

  • Identify and Categorize Sensitive Data: To efficiently protect data, you must know what types of data you have. Data discovery technology scans data repositories and reports findings, providing visibility.
  • Implement Data Encryption: Encryption provides a basic safeguard for sensitive data in storage and transit.
  • Limit Access to Sensitive Data: Restricting user access to only necessary data is an effective way to prevent data loss.
  • System Hardening: Regular security awareness training for employees helps prevent data loss, where they can identify suspicious behavior and report it.
  • Monitor High-Value Data: Understanding data usage and risky behavior is critical for creating appropriate policies that mitigate data loss risk.
  • Maintain Systems: Keeping software and hardware updated is crucial for data security.
  • Automate DLeakP Processes: Automating DLeakP processes helps reduce human error and ensures policy consistency.
  • Regular Employee Training: Regular security awareness training for employees is crucial for preventing data loss. Employees should be trained to identify and report suspicious behavior.

Conclusion

Data Loss Prevention (DLP) and Data Leak Prevention (DLeakP) are two techniques organizations deploy to shield their essential data. These terms, though frequently used as substitutes for each other, denote different concepts. DLP revolves around shielding data from active threats that have the potential to harm or annihilate it, while DLeakP concerns itself with controlling data flow within and beyond the organization’s boundaries. By adhering to the optimal practices discussed in this piece, companies can boost their data security and fortify their defenses against potential dangers.


Prasanna Peshkar is a cybersecurity researcher, educator, and cybersecurity technical content writer. He is interested in performing audits by assessing web application threats, and vulnerabilities. He is interested in new attack methodologies, tools and frameworks. He also spends time looking for new vulnerabilities, and understanding emerging cybersecurity threats in the blockchain technology. He is also a regular writer at Bora. 


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