Data loss prevention (DLP) is an essential component of a comprehensive cybersecurity posture. DLP solutions protect an organization’s critical intellectual property and sensitive data from being misused or leaked by unauthorized individuals. This type of security software has become increasingly important to address the expanding attack surface created by a remote and mobile workforce.
A DLP platform provides enhanced data protection from both external threat actors and insider threats. An effective DLP tool protects your organization from external cybercriminals, insiders who attempt to leak data maliciously, and accidental data leaks by trusted employees.
Many DLP solutions are available and provide varying feature sets and levels of protection. In this post, we'll take a look at Forcepoint’s data loss prevention solution and see how the Reveal platform from Next offers customers additional benefits.
Forcepoint’s data loss prevention solution is designed to help organizations protect valuable information and intellectual property without disrupting the user experience. The software consists of four complementary components that work together to protect company data resources.
Forcepoint’s DLP offerings are available in 2 versions. Customers can opt for DLP for Compliance or DLP for Intellectual Property (IP) Protection.
Let’s look at some of the features that make Forcepoint’s DLP software an effective tool for protecting valuable data resources.
The Reveal Platform by Next offers customers significant benefits over Forcepoint’s solution and other similar tools on the market. Organizations can enjoy the following advantages by implementing Reveal to protect their data assets.
Automated enforcement of the organization’s data handling policies ensures that sensitive or high-value information cannot be used by unauthorized personnel. Users are restricted from violating the policy to guard against accidental insider data leaks.
An AI-powered assistant enhances security analysis to prevent data loss and mitigate insider threats. Security teams benefit from optimized workflows and reduced time to contain and resolve threats for more effective data loss prevention.
Advanced next-gen endpoint agents powered by machine learning technology are used to categorize data at the point of risk.
Reveal starts baselining data activity at deployment and employs multiple behavioral analytics algorithms to define typical versus anomalous behavior. The solution does not require a connection to a separate analysis engine for more effective endpoint data protection.
Reveal continuously promotes enhanced security consciousness throughout the organization by providing user training at the point of risk. Individuals who attempt to take an action that violates the company’s data handling policy will be prohibited from performing the activity.
Users also receive a message informing them of the specific violation and referring them to the organization’s acceptable use policy. Emphasizing why an activity was restricted rather than simply stopping it increases security awareness and helps minimize or eliminate the risks of unintentional insider threats.
To learn more about how this cutting-edge DLP solution offers a better alternative to Forcepoint data loss prevention, talk to the experts at Next and see Reveal in action with a free demo.
What are unintentional insider risks to sensitive data resources?
Unintentional insider risks to sensitive data resources are activities that inadvertently expose high-value data to unauthorized sources.
For example, an individual may send a colleague sensitive information over a public network without encrypting it first. Companies should perform an insider risk assessment to identify the level of risk posed by their employees.
Why is endpoint data loss prevention important to support a remote workforce?
Data loss prevention is important when supporting a remote workforce due to the expanded attack surface available to threat actors. Cybercriminals can target remote devices that are outside the corporate firewall and put data at risk.
Endpoint DLP ensures that mobile employees do not accidentally or maliciously leak or misuse company information.
How is machine learning used to enhance Reveal’s effectiveness?
Reveal's smart agent uses machine learning to enhance its effectiveness as a DLP solution. The agent begins baselining user activity at deployment and employs advanced behavioral analytics algorithms to define typical and anomalous behavior.
Over time, machine learning optimizes the rules that differentiate acceptable and unacceptable behavior to address new threats to intellectual property.