Confidential Data Discovery With Quantitative Network Risk Analysis
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Solution Overview
Problem
Existing technologies fail to comprehensively identify and quantify the risk associated with confidential data at rest in communication networks, lacking the ability to calculate information and cyber risk, and identify gaps in data protection.
Innovation Solution
A system comprising client devices, a communication network, and a communication unit with a crawler module, data repository, artificial intelligence module, and reporting module, which scans and analyzes data in various formats to categorize and quantify risk, providing potential liability and insurance value based on predefined parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations use numerous disparate tools and time-consuming processes to secure confidential data, then data security coverage is improved, but operational efficiency deteriorates
Solution Approach 1:
The patent combines multiple disparate data security tools and processes into a single integrated automated system that performs data discovery, classification, risk assessment, and compliance monitoring simultaneously, thereby maintaining comprehensive security coverage while dramatically improving operational efficiency
Solution Approach 2:
The system performs preliminary automated actions by continuously scanning, identifying, and classifying confidential data before threats occur, and proactively assessing risks and generating compliance reports, eliminating the need for time-consuming manual security processes
2Measurement precision
If organizations implement comprehensive data identification and risk quantification systems, then compliance accuracy is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal automated system that performs multiple functions including data discovery, classification, risk assessment, and compliance monitoring across various regulations (GDPR, HIPAA, PCI-DSS, etc.) within a single platform, improving compliance accuracy without proportionally increasing system complexity
Solution Approach 2:
The system performs self-service by automatically scanning networks, identifying confidential data, classifying it according to multiple regulatory frameworks, assessing risks, and generating compliance reports without requiring manual configuration or intervention, thereby achieving high compliance accuracy with manageable complexity
3Ease of operation
If organizations fail to quantify information and cyber risk, then regulatory compliance is maintained at minimal level, but organizational liability exposure increases
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor confidential data, assess cyber risks, and provide quantitative risk metrics and compliance status reports to organizations, enabling them to understand and address liability exposures while maintaining regulatory compliance through informed decision-making
Data Source
AI summary
Present invention relates to systems and methods for calculation of information and cyber risk posed by the systems and methods that process data and their automated non-compliance verification and information and cyber risk posed by non-compliance. Disclosed is a system (100) and a method (200) for calculation of information and cyber risk by identifying sensitive electronic information stored in client devices (10) like desktops, laptops, mobile devices and databases of shared network drives or cloud environments connected through a communication network (20). The system (100) is capable of identifying the data at rest stored in various file formats such as word, excels, csv, pdf, power point, database file formats and compressed file formats. The method (200) calculates information and cyber risk and there identifies the potential liability or insurance value based on volume and value of data and compliance with corporate policies for data protection and potential areas of non-compliance.