Data Loss Prevention (DLP) is designed to prevent critical information from being leaked by end users – either inadvertently or deliberately – outside of an organization’s network. The impact of data loss and leaks is staggering – the Ponemon Institute’s Cost of a Data Breach report puts the total cost of a breach at $3.92 million dollars and each lost record representing a cost of $150.
A DLP system can be configured to respond based on pre-defined policy and rules to enable analysts to most efficiently investigate and respond to the alerts and prevent future incidents. However, the DLP system must be continuously monitored to assure proper configuration to prevent data leaks. A medium sized organization could experience hundreds of DLP violations per day; augmenting DLP triage and response processes with automation is critical to mitigate risk.
DTonomy’s AI Assisted SOAR platform contains playbooks for DLP configuration workflows to provide real time critical information about the robustness of the system’s security. When deployed in conjunction with a DLP solution, DTonomy’s playbooks autonomously and continuously test the validity of the system to ensure that a strong security strategy is being enforced while enabling security analysts to more quickly triage and respond to DLP alerts.