DLP Teams

DLP teams work hard to prioritize actions on a daily basis to improve data protection, but incident analysis, triage and remediation, along with policy refinement and other related tasks all compete for attention.

Data protection programs often encompass numerous manual workflows – whether analyzing individual incidents for abnormal versus acceptable behaviors, or assessing policy effectiveness across multiple stakeholders via email. Automating these time-consuming processes using analytics that determine baselines of normal activity using existing telemetry offers a tremendous advantage, detecting both benign and dangerous anomalies and prioritizing actions to address today’s greatest risks.

Accelerating Incident Triage

Bay Dynamics Risk Fabric automatically determines baseline behavior for both users and machines via advanced User & Entity Behavior Analytics (UEBA) that integrate with existing security infrastructure. Leveraging both supervised and unsupervised machine learning, Risk Fabric rapidly detects anomalies that represent real-world threats to data security, differentiating between nefarious activities and non-malicious incidents to enable targeted remediation.

Streamlining Policy Review

Security policy creation and review is often a highly manual process distributed between numerous stakeholders. Initial deployment and subsequent tuning can be onerous, involving largely manual analysis shared across security, operations and business stakeholders made. Risk Fabric consolidates and automates this process into unified workflows where policies can be tested, refined and revised in only days, massively accelerating the entire process.

Collaborating with Business on Data Protection Effectiveness

Now more than ever, business units that own sensitive information are under pressure to stay involved with security oversight and ensure ongoing standards compliance. Risk Fabric was purpose built to ensure clear communication and collaboration with every relevant audience, visualizing critical security trends and metrics to allow numerous stakeholders to play their important roles in driving optimal data protection.

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