Machine Learning False Positives

Visibility: Accurately, discover sensitive data; detect and address broken business process, or insider threats including sensitive data breach attempts.

Protection: Automate data protection, breach prevention and incident response both on and off the network; for example, find and quarantine sensitive data within files exposed on user workstations, FileShares and cloud storage.

Notification: Alert and educate users on violations to raise awareness and educate the end user about cybersecurity and corporate policies.

Education: Start target cyber-security training; e.g., identify end-users violating policies and train them.

• Employees and organizations have knowledge and control of the information leaving the organization, where it is being sent, and where it is being preserved.
• Ability to allow user classification to give them influence in how the data they produce is controlled, which increases protection and end-user adoption.
• Control your data across your entire domain in one Central Management Dashboard with Universal policies.
• Many levels of control together with the ability to warn end-users of possible non-compliant – risky activities, protecting from malicious insiders and human error.
• Full data discovery collection detects sensitive data anywhere it is stored, and provides strong classification, watermarking, and other controls.
• Delivers full technical controls on who can copy what data, to what devices, what can be printed, and/or watermarked.
• Integrate with GRC workflows.  

• Reduce the risk of fines and non-compliance.
• Protect intellectual property and corporate assets.
• Ensure compliance within industry, regulatory, and corporate policy.
• Ability to enforce boundaries and control what types of sensitive information can flow where.
• Control data flow to third parties and between business units.