Cloud User Reputation Analysis for Data Exposure Control
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Solution Overview
Problem
In cloud computing environments, businesses face challenges in ensuring that employee access settings for data objects do not inadvertently expose sensitive information to unauthorized users, as existing systems lack practical means to enforce desired privacy levels.
Innovation Solution
A reputation analysis system that collects and analyzes user behavior data from cloud computing environments to determine exposure characteristics, applying rules to assess user reputation and generate notifications for remedial actions to mitigate excessive data object exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If employees are allowed to independently modify access settings for data objects, then ease of operation is improved, but data security deteriorates due to potential excessive exposure
Solution Approach 1:
The system continuously monitors user behavior and automatically adjusts access settings based on reputation scores. When a user exhibits risky behavior patterns, the system provides feedback by restricting their ability to modify settings or by automatically tightening access controls, thus preventing data exposure while maintaining operational ease for trustworthy users
Solution Approach 2:
The system dynamically changes access control parameters based on user reputation metrics. Users with high reputation scores retain full ability to modify settings, while users with low scores have their modification capabilities restricted or require additional approval, effectively adapting security parameters to individual user risk profiles
2Object-affected harmful factors
If access settings are restricted to prevent data exposure, then data security is improved, but ease of operation deteriorates as employees cannot independently manage their data
Solution Approach 1:
The system performs preliminary analysis of user behavior patterns and establishes reputation scores before security restrictions are applied. By proactively identifying at-risk users through behavioral analysis, the system can prevent data exposure issues before they occur, rather than imposing blanket restrictions on all users
Solution Approach 2:
Security restrictions are applied locally to individual users based on their specific reputation scores and behavior patterns, rather than uniformly across all employees. This allows the system to maintain data security for at-risk users while preserving full operational autonomy for trustworthy users
3Object-affected harmful factors
If the system monitors and analyzes user behavior to determine reputation, then data security is improved through better control, but device complexity increases
Solution Approach 1:
The reputation analysis system automatically collects behavior data, analyzes patterns, calculates reputation scores, and adjusts access settings without requiring manual intervention from security administrators. The system serves itself by continuously monitoring and adapting, reducing operational complexity despite the sophisticated analysis performed
Solution Approach 2:
The reputation analysis system serves multiple functions: it monitors user behavior, analyzes security risks, calculates reputation scores, communicates with users, and automatically adjusts access controls. By consolidating these diverse functions into a single integrated system, the patent reduces overall device complexity compared to having separate systems for each function
4Object-affected harmful factors
If the system generates notifications and enforces remedial actions, then data security is improved through compliance enforcement, but ease of operation deteriorates due to additional constraints on users
Solution Approach 1:
The system applies remedial actions selectively based on the severity and frequency of policy violations. For minor or first-time violations, the system may issue warnings or notifications without imposing immediate restrictions. For repeated or severe violations, progressively stronger remedial actions are applied, balancing compliance enforcement with minimal disruption to legitimate user workflows
Data Source
AI summary
User reputation regarding exposure of data objects in a cloud computing environment is determined. Behavioral information, which indicates behavior of a user for a cloud computing environment corresponding to one or more data objects in the cloud computing environment that are associated with the user, is analyzed. Based on analyzing the behavior information, a plurality of characteristics for the user that indicate exposure of the data object(s) associated with the user is determined. Each of the plurality of characteristics reflects the behavior of the user pertaining to the one or more data objects. Based on compliance of the plurality of characteristics with corresponding ones of a plurality of rules, a reputation of the user for exposing data objects in the cloud computing environment is determined. The reputation of the user is indicated to an entity with which the user is associated.