AI-Based Periodic Privacy Profiles for Network Data Exposure Control
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Solution Overview
Problem
Computing devices connected to the Internet expose sensitive data that can be exploited by unauthorized network hosts, leading to vulnerabilities and data breaches.
Innovation Solution
A data protection platform using artificial-intelligence-based modeling dynamically generates and modifies artificial profiles to control data exposure, obfuscating identifying information and preventing unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing devices connect to the Internet to access webpages and services, then network functionality and information access are improved, but data privacy elements are exposed to unauthorized network hosts
Solution Approach 1:
The patent introduces an intermediary system that sits between the computing device and network hosts, intercepting and modifying network traffic. This intermediary dynamically alters data privacy elements in communications, preventing direct exposure of真实 information to unauthorized hosts while maintaining network connectivity functionality
Solution Approach 2:
The system creates artificial copies of data privacy elements that resemble real data but contain obscured or fictionalized information. These artificial profiles are presented to network hosts instead of actual device identifiers, maintaining the appearance of legitimate data while protecting the underlying sensitive information
2Reliability
If data privacy elements are exposed for network communication, then network functionality is maintained, but vulnerability to exploitation by unauthorized hosts increases
Solution Approach 1:
The system applies preliminary protective measures by pre-processing data privacy elements before they reach unauthorized hosts. Artificial profiles are generated in advance with built-in obfuscation, and constraints are established beforehand to prevent the exposure of exploitable information while maintaining communication reliability
3Object-affected harmful factors
If artificial profiles are dynamically generated and modified, then data exposure is controlled and privacy is enhanced, but system complexity increases
Solution Approach 1:
The system implements dynamic artificial profile generation where profile characteristics change over time and in response to different network interactions. This dynamic approach allows the same computing device to present different artificial profiles to different hosts, enhancing privacy control while managing complexity through adaptive rather than static configurations
Solution Approach 2:
The system modifies various parameters of artificial profiles including data elements, constraints, and presentation characteristics. By changing these parameters dynamically based on network context, the system achieves fine-grained control over data exposure without requiring complete system redesign for each scenario
Data Source
AI summary
Systems and methods for periodically modifying data privacy elements are provided. The systems and methods may identify a set of data privacy elements. A data privacy element can characterizes a feature of a computing device and can be detectable by a network host. A first artificial profile can be generated by modifying a first data privacy element based on an artificial profile model that defines a relationship associated with one or more constraints between the set of data privacy elements. Subsequent to generating the first artificial profile, a second artificial profile can be generated by periodically modifying a second data privacy element in accordance with the relationship defined by the artificial profile model. The computer device can be masked from being identified by the network host by sending the second artificial profile including the second data privacy element to a requested network location.