AI-Generated Artificial Profiles for Data Privacy Exposure Control
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Solution Overview
Problem
Computing devices connected to the Internet expose data that can be accessed by both authorized and unauthorized network hosts, posing privacy risks and vulnerabilities that can lead to data breaches.
Innovation Solution
A data protection platform using artificial-intelligence-based modeling dynamically creates, modifies, and validates artificial profiles to control data exposure, obfuscating sensitive information by generating realistic yet inaccurate data privacy elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing devices connect to the Internet to enable network communication and data access, then network functionality and connectivity are improved, but data privacy exposure and vulnerability to unauthorized access increase
Solution Approach 1:
The patent introduces an intermediary system that sits between the computing device and the network, intercepting and modifying data transmissions. This intermediary processes outgoing data to remove or obfuscate privacy elements while maintaining legitimate network communication functionality, thus resolving the contradiction between connectivity and privacy protection.
Solution Approach 2:
The system creates artificial copies of data privacy elements that can be exchanged instead of real identifying information. By generating synthetic data that mimics the structure and format of actual privacy elements, the system enables network communication while preventing exposure of genuine sensitive information.
2Ease of operation
If data privacy elements are exposed for network communication purposes, then network operation functionality is maintained, but unauthorized hosts can exploit vulnerabilities to execute data breaches
Solution Approach 1:
The system applies preliminary protective measures by automatically identifying and removing vulnerable data privacy elements before they can be exploited by unauthorized hosts. This preemptive approach neutralizes potential security threats while maintaining necessary network operational functionality.
Solution Approach 2:
The system converts the potentially harmful exposure of data privacy elements into a benefit by using artificial intelligence to generate synthetic replacements. These artificial elements serve the same communication purpose while eliminating the security risk, thus transforming a vulnerability into a protective mechanism.
3Object-affected harmful factors
If artificial intelligence-based modeling is used to dynamically create and modify artificial profiles, then data privacy protection is improved, but system complexity increases
Solution Approach 1:
The AI-based system operates autonomously to identify, generate, and manage artificial profiles without requiring manual intervention. The system self-adjusts and adapts to different communication scenarios automatically, reducing the operational burden despite the underlying complexity of the AI modeling processes.
Solution Approach 2:
The system dynamically adjusts parameters of artificial profiles based on communication context and security requirements. By changing parameters such as data element composition, profile structure, and obfuscation levels, the system maintains effective privacy protection while adapting to different operational conditions without requiring complete system redesign.
Data Source
AI summary
Systems and methods for controlling the exposure of data privacy elements are provided. The systems and methods may generate an artificial profile model. The artificial profile model may include a constraint for generating new artificial profiles. A signal may be received indicating that a computing device is requesting access to a network location. One or more data privacy elements associated with the computing device can be detected. An artificial profile can be determined for the computing device. The artificial profile may be usable to identify the computing device. The one or more data privacy elements may be automatically modified according to the constraint included in the artificial profile model. The method may include generating a new artificial profile for the computing device. The new artificial profile may include the modified one or more data privacy elements. The new artificial profile may mask the computing device from being identified.