DFLabs Unveils Machine Learning Powered First Responder Automation for Security Operations
DFLabs announced today the release of its new Playbook Recommendation and Intelligent Selection Mechanism (DF-PRISM), enhancing DFLabs security orchestration, automation and response with incorporated proprietary machine learning. The system uses algorithms and patent-pending advanced methods to detect operational intelligence such as security incident and resolution data to recommend playbooks and actions based on historical incident response activities. This approach minimizes the resources and time required to successfully analyze and respond to ongoing incidents while maximizing the effectiveness and efficiency of security teams.
“In developing DF-PRISM, we built a technology that enables users and the system to learn together and lets humans determine their level of involvement in responding to and managing threats,” said Dario Forte, chief executive officer and founder, DFLabs. “Users get immediate value by tracking and responding to threats, then over time the system builds a knowledge base of responses that can be relied on to automatically manage the entire incident response process.”
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