Outbound Email DLP Incident Alerting System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data security measures fail to effectively prevent data leakage through outbound emails, as they lack real-time detection and decentralized management capabilities, leading to potential data breaches in large enterprises.
Innovation Solution
A computer-implemented method and system that detects outbound email violations of data leakage prevention (DLP) rules, automatically alerts relevant enterprise members, solicits justification, and receives responses to determine authorization, with whitelisting capabilities to exempt certain employees from DLP rules, leveraging natural language processing for adaptive content analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data security measures are implemented, then data integrity is enforced, but real-time detection and response capabilities are lacking
Solution Approach 1:
The system performs preliminary actions by pre-configuring DLP rules, alerting protocols, and response workflows before incidents occur. When an incident is detected, the pre-established framework enables immediate automated response, eliminating the need for manual analysis and decision-making delays.
Solution Approach 2:
The system implements continuous feedback loops where incident detection automatically triggers alerts to security personnel, who then provide responses that feed back into the system. This feedback mechanism enables real-time adjustment of security measures and continuous improvement of detection accuracy.
2Manufacturing precision
If centralized DLP management is used, then policy enforcement is consistent, but investigation processes are slow and centralized
Solution Approach 1:
The system segments the centralized DLP management into distributed components: local agents on email servers detect incidents, security personnel at different locations receive and investigate alerts, and responses are collected from multiple sources. This segmentation maintains policy consistency while enabling parallel investigation processes that accelerate response times.
Solution Approach 2:
The system adds a temporal dimension to DLP management by implementing real-time detection and alerting, transforming the traditionally batch-processed centralized management into a continuous, multi-dimensional process that operates across time and spatial boundaries simultaneously.
3Object-affected harmful factors
If DLP rules are applied to all outbound emails, then data leakage is prevented, but legitimate business communications may be blocked
Solution Approach 1:
The system introduces an intermediary alerting mechanism that sits between DLP rule enforcement and communication blocking. When a potential violation is detected, the system generates an alert for human review rather than automatically blocking the email, allowing legitimate communications to proceed while maintaining security oversight.
Solution Approach 2:
The system applies DLP rules partially by focusing monitoring and alerting on high-risk patterns while allowing lower-risk communications to proceed with minimal intervention. This selective application maintains security for critical threats while preserving communication efficiency for routine business emails.
Data Source
AI summary
The present disclosure describes a computer-implemented method that includes: detecting an incident that an outbound email violates a data leakage prevention (DLP) rule of an enterprise, wherein the DLP rule specifies contents that are reserved for within the enterprise; automatically alerting one or more members of the enterprise of the incident based on a report detailing the incident; and receiving a response from each of the one or more members of the enterprise.