Privacy Management System Integrating Data Loss Prevention Tools

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Solution Overview

Problem

Current systems lack effective methods for efficiently monitoring compliance with corporate privacy policies and applicable privacy laws, particularly in identifying sensitive data within data structures and populating suitable data structures managed by a privacy management computer system, which hampers organizations' ability to manage personal data effectively and respond to breaches.

Innovation Solution

A computer-implemented data processing system that receives campaign data for privacy campaigns, calculates a risk level based on weighted factors, and generates an audit schedule, using graphical user interfaces to input and display campaign information, facilitating collaboration, and automatically populating fields with data input history to streamline the privacy compliance process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual monitoring of privacy compliance is performed, then flexibility in handling privacy policies can be maintained, but the efficiency and accuracy of identifying sensitive data deteriorates

Engineering Contradiction:

Improveflexibility in handling privacy policiesVSAvoidefficiency of identifying sensitive data

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system enables automated self-monitoring of privacy compliance by using data loss prevention tools to automatically identify sensitive data, assess risks, and generate audit schedules without requiring manual intervention for each privacy campaign, thus improving efficiency while maintaining policy flexibility through configurable parameters

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processes of privacy monitoring are replaced with automated computational systems that use algorithms to calculate risk levels, identify sensitive data patterns, and generate compliance reports, significantly improving the efficiency and accuracy of sensitive data identification

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If comprehensive privacy monitoring is implemented across all data structures, then compliance accuracy is improved, but system complexity increases

Engineering Contradiction:

Improvecompliance monitoring accuracyVSAvoidsystem integration complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The monitoring system is segmented into modular components including data loss prevention tools, privacy management systems, and risk assessment modules that can be independently configured and integrated, reducing overall system complexity while maintaining comprehensive monitoring capability across multiple data structures

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system employs universal data structures and standardized interfaces that can handle multiple types of sensitive data (personally identifiable information, sensitive personal data, etc.) through a single integrated platform, reducing complexity by avoiding the need for separate specialized systems for each data type

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Productivity

If automated risk calculation is performed for all privacy campaigns, then productivity is improved, but use of energy increases

Engineering Contradiction:

Improveefficiency of privacy compliance processingVSAvoidcomputational energy consumption

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system performs automated risk calculation selectively based on risk thresholds and data sensitivity levels, applying full automated processing only to high-risk privacy campaigns while using simplified assessment methods for lower-risk campaigns, thereby improving overall productivity without proportionally increasing energy consumption across all campaigns

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11004125B2Data processing systems and methods for integrating privacy information management systems with data loss prevention tools or other tools for privacy design

Publication Date: 2021.05.11 ONETRUST LLC

AI summary

Computer implemented methods, according to various embodiments, comprise: (1) integrating a privacy management system with DLP tools; (2) using the DLP tools to identify sensitive information that is stored in computer memory outside of the context of the privacy management system; and (3) in response to the sensitive data being discovered by the DLP tool, displaying each area of sensitive data to a privacy officer (e.g., similar to pending transactions in a checking account that have not been reconciled). A designated privacy officer may then select a particular entry and either match it up (e.g., reconcile it) with an existing data flow or campaign in the privacy management system, or trigger a new privacy assessment to be done on the data to capture the related privacy attributes and data flow information.