SaaS Provider Security Assessment Through Network Path Discovery
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Solution Overview
Problem
Existing systems fail to adequately monitor and protect sensitive data stored by Software as a Service (SaaS) providers, leading to potential public exposure of confidential information.
Innovation Solution
A computing system assesses network paths and data locations of SaaS providers to identify and evaluate the presence of sensitive data, taking automated actions to ensure data privacy and security, including generating a list of network paths, analyzing data for sensitive information, and implementing remediation measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated assessment of SaaS provider data management is implemented, then data security and privacy protection are improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent introduces an intermediary assessment system that acts as a mediator between clients and SaaS providers. This system automatically evaluates data management practices by analyzing network paths, data locations, and access controls without requiring direct intervention from either party. The intermediary nature resolves the contradiction by providing professional security assessment capabilities while maintaining simplicity for end users.
Solution Approach 2:
The assessment system enables SaaS providers to self-evaluate their data management practices through automated scanning and analysis of their own systems. By allowing providers to independently assess and remediate issues, the system improves data security without requiring complex external monitoring infrastructure, thus reducing overall system complexity.
2Measurement precision
If comprehensive monitoring of all SaaS provider data locations is performed, then detection precision of sensitive data is improved, but assessment time and computational resources increase
Solution Approach 1:
The patent segments the assessment process into distinct phases: initial automated scanning to identify potential data locations, followed by targeted evaluation of sensitive data at those locations. This segmentation allows comprehensive monitoring without requiring continuous full-system analysis, thereby reducing assessment time while maintaining detection precision through focused examination of high-risk areas.
Solution Approach 2:
The system performs partial assessment by focusing computational resources on identifying and evaluating only those data locations that are most likely to contain sensitive information. Rather than uniformly analyzing all data, the system applies excessive action selectively to high-priority areas, achieving high detection precision with reduced overall assessment time and resource consumption.
3Ease of operation
If manual curation and reverse engineering of storage practices are avoided, then ease of operation is improved, but automation capability must be enhanced
Solution Approach 1:
The patent replaces manual mechanical processes (curation and reverse engineering) with automated computational systems that scan network paths, analyze data structures, and identify storage practices programmatically. This substitution dramatically improves ease of operation by eliminating the need for expert manual intervention while enhancing automation capability through sophisticated algorithms that learn and adapt to different SaaS provider configurations.
Data Source
AI summary
This disclosure describes techniques that include assessing whether various service providers, such as cloud service providers or SaaS providers, are properly maintaining sensitive data (e.g., private, confidential, and/or non-public information) that is entrusted to them. In one example, this disclosure describes a method that includes collecting, by a computing system, information about interactions with a service provider computing system; identifying, based on the information about the interactions, a plurality of network paths, each associated with a data object accessed at the service provider computing system; requesting, based on the plurality of network paths, data from the service provider computing system; receiving a response; determining, based on the response, whether the response includes sensitive information; and taking action based on whether the response includes sensitive data.