Chat-Based Data Loss Prevention Alerting
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Solution Overview
Problem
Current data loss prevention (DLP) services require administrators to repeatedly log into a user interface for each instance of detected private information, leading to inefficiencies when monitoring numerous data sources and users, as they need to manually take actions on detected private data without real-time notification capabilities.
Innovation Solution
A DLP service integrates with a chat service to send alerts directly to users or groups, enabling real-time notifications and allowing corrective actions without requiring administrators to access the DLP service interface, using a machine learning model for detection and a chat service interface for broadcasting alerts and facilitating actions like quarantining or deleting private information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If administrators manually log into the user interface for each detected private information instance, then they can take corrective actions, but the process becomes time-consuming and inefficient when monitoring numerous data sources
Solution Approach 1:
The patent introduces a chat service as an intermediary between the DLP system and administrators. Instead of administrators directly accessing the DLP user interface for each alert, the system sends notifications through the chat service, which then distributes alerts to relevant users via their preferred communication channels. This intermediary layer eliminates the need for repeated manual logins and streamlines the notification process.
Solution Approach 2:
The system enables self-service by automatically routing notifications through the chat service without requiring administrator intervention to access the DLP interface. The chat service autonomously receives alerts from the DLP system and distributes them to appropriate users, allowing the notification process to serve itself without human overhead.
2Speed
If the DLP service sends detailed alerts to all users, then real-time notification is achieved, but information overload and privacy concerns arise
Solution Approach 1:
The patent applies local quality by customizing alert distribution based on user roles, data sensitivity, and relevance. Different users receive different subsets of alerts tailored to their responsibilities and clearance levels. This ensures that each user receives appropriate information without being overwhelmed by unrelated alerts or exposed to unnecessary sensitive data.
Solution Approach 2:
The alert distribution system segments notifications by user group, data type, and sensitivity level. Instead of broadcasting all alerts to all users, the system divides alerts into targeted segments and delivers them only to relevant audiences. This segmentation maintains real-time notification speed while preserving information quality and privacy.
Data Source
AI summary
Chat-based systems and methods for data loss prevention are described. In one embodiment, a method includes receiving an enable command from a chat service by a data loss prevention service, scanning data from a data source with the data loss prevention service in response to the enable command to detect private information in the data, generating an alert for the private information by the data loss prevention service, and sending the alert to the chat service to cause the chat service to broadcast a chat alert to a group of users.