Insider Threat and DLP

Insider Threat and DLP

Insider threat refers to a security risk posed by individuals within an organization who have access to sensitive information or systems. This could include employees,  third-party vendors,  contractors and malware. Insider threats can occur unintentionally (e.g., through careless actions or by falling for phishing scams) or intentionally (e.g., theft of data for personal gain or sabotage).

DLP (Data Loss Prevention) is a technology that helps organizations prevent sensitive data from being leaked or stolen. DLP solutions monitor and control the flow of sensitive data, such as credit card numbers, Social Security numbers, or unstructered confidential business information, and can alert administrators or block transfers if they violate the organization’s security policies. By implementing DLP, organizations can mitigate the risk of insider threats and data breaches.

How does GTB’s DLP that Works^tm stop insider threats?

GTB DLP stops insider threats by monitoring and controlling the flow of sensitive data within an organization’s network, both on and off premises. This is achieved through the following steps:

Identification: GTB DLP systems are configured to identify sensitive data based on specific criteria, such as credit card numbers, Social Security numbers, or confidential business information.

Monitoring: GTB DLP systems continuously monitor the flow of data, both in and out of the organization’s network, to ensure that sensitive data is not being transmitted or accessed inappropriately.

Enforcement: If a violation is detected, GTB DLP systems can either alert administrators or automatically block the transfer of sensitive data, depending on the organization’s security policies.

By implementing GTB’S DLP that Works^tm solutions, organizations can reduce the risk of insider threats by preventing sensitive data from being leaked or stolen, either intentionally or unintentionally. Additionally, DLP can also help organizations detect, prevent,  and respond to data breaches more quickly, and find those actors exfiltrating sensitive data, thus reducing the potential damage and improving overall security.