Data Loss Prevention

Data Loss Prevention (DLP)

Keep your sensitive data secure and prevent the unauthorized use and transmission of your confidential information.

Data Loss Prevention Tailored to Your Organizational Needs

Our DLP program services can help you understand how to properly plan, deploy and tune all aspects to control sensitive data exiting the network and/or your endpoints.

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DLP Isn’t a Product. It’s a Methodology.

Gaining full visibility into day-to-day data movement within your organization will lead to minimizing insider threats and external attacks on your information infrastructure.

Policy-driven technology can:

Assist in the detection and alerting of potential data breaches
Classify confidential, business and regulated data in alignment with your organization’s policies or regulatory requirements such as PCI, HIPAA, GDPR and more

DLP with a White Glove Approach

Our end-to-end DLP service provides you with the confidence of knowing your sensitive data is safe within the confines of your environment. Identifying proprietary workflows and exceptions allow for a customized program optimized for your organization.

Data Control on the Endpoint

End-user activity threats such as cut/copy/paste, print, removable drives and print screen operations are some potential ways data can be exfiltrated on an endpoint. Protection is typically applied via agent-based content analysis within a user’s working environment (PC, laptop or other) and monitors/ blocks potential breaches as defined by a rule-based policy.

Data in Motion

Traffic that moves through the corporate network includes confidential data that must be captured and inspected. Controls for network protocols, email, web and file transfers are often seen in corporate networks as a precautionary measure, due to the sheer volume of day-to-day operations that involve sensitive data through these channels.

Data at Rest

It is important to scan confidential information and detect data leaks from storage targets, including file servers and cloud platforms. This critical perspective focuses on identifying stagnant data as well as protecting sensitive information in the data warehouse, as it is here that data spends most of its time.