What is the Difference Between Network DLP and Endpoint DLP

The main difference between Network DLP and Endpoint DLP is that Network DLP refers to securing the organization’s network communications, while Endpoint DLP refers to securing intellectual property and ensure compliance.

Overall, Network DLP and Endpoint DLP are two types of DLP. Here, data loss prevention (DLP) is the process of detecting data breaches/data ex-filtration transmissions and preventing them by monitoring, detecting and blocking sensitive data in endpoint actions, network traffic or in data storage.

Key Areas Covered

1. What is Network DLP
     -Definition, Functionality
2. What is Endpoint DLP
    -Definition, Functionality
3. Difference Between Network DLP and Endpoint DLP
    -Comparison of key differences

Key Terms

DLP, Endpoint DLP, Network DLP

Difference Between Network DLP and Endpoint DLP - Comparison Summary

What is Network DLP

Network Data Loss Prevention (Network DLP) is a technology for protecting network communications such as web applications, emails, and data transfer mechanisms of the organization. It helps to prevent the loss of sensitive information of the network. Moreover, it allows the company to encrypt data and to block risky information flows in a methodical manner to monitor and control the flow of data over the network according to the regulatory compliance.

Difference Between Network DLP and Endpoint DLP

Furthermore, network DLP  provides multiple facilities. It allows inspecting and controlling traffic on email, webmail and web applications. It also avoids sensitive data loss via the network. Furthermore, it checks email subjects, messages and attachments for sensitive content. Additionally, it informs users and administrators when network traffic violates corporate data protection policies and enforce policy-based monitoring and blocking of web applications.

What is Endpoint DLP

Endpoint helps to safeguard intellectual property and ensure compliance. Endpoint DLP provides a number of services. It protects sensitive data in the cloud or at the endpoints. It also helps to track user behaviors. In other words, it monitors and addresses daily risky actions. Some of them are emailing, screen capturing, uploading to cloud and device controlling. Moreover, Endpoint DLP allows the user to run endpoint discovery scans and to perform self-remediation actions. Another important feature is that it provides wider threat protection.

Difference Between Network DLP and Endpoint DLP

Definition

Network DLP is a technology for securing an organization’s network communications while Endpoint DLP is a technology to safeguard intellectual property and to ensure compliance. Thus, this is the fundamental difference between network DLP and endpoint DLP.

Association

Furthermore, network DLP refers to the prevention of data loss during network traffic while Endpoint DLP refers to the prevention of data loss while in general use. Hence, this is another difference between network DLP and endpoint DLP.

Conclusion

In brief, two types of DLP are Network DLP and Endpoint DLP. The main difference between Network DLP and Endpoint DLP is that Network DLP refers to securing the organization’s network communications while Endpoint DLP refers to securing intellectual property and ensure compliance.

References:

1.“What Is Network Data Loss Prevention?” Digital Guardian, 7 Sept. 2018, Available here.
2.“Endpoint DLP.” Digital Guardian, 1 Feb. 2019, Available here.
3.“McAfee DLP Endpoint.” DLP Endpoint – Endpoint Data Loss Prevention | McAfee Products, Available here.
4.“Data Loss Prevention Software.” Wikipedia, Wikimedia Foundation, 15 May 2019, Available here.

Image Courtesy:

1.”Partial map” By The Opte Project – Originally from the English Wikipedia; description page is/was here (CC BY 2.5) via Commons Wikimedia

About the Author: Lithmee

Lithmee holds a Bachelor of Science degree in Computer Systems Engineering and is reading for her Master’s degree in Computer Science. She is passionate about sharing her knowldge in the areas of programming, data science, and computer systems.

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