Privacy Protection via Synthetic Link Distribution
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Solution Overview
Problem
Current web privacy protection systems, such as Tor and VPN, degrade user utility and personalized services while attempting to anonymize web browsing history, leading to hampered predictability of online activity and increased processing power loss.
Innovation Solution
A computer-based privacy system that generates and modifies internet topics by determining and selecting a number of links for each topic, balancing privacy levels with utility loss using a tradeoff coefficient, and selecting links from random users outside of a friend list to create a uniform distribution of browser history, thereby enhancing user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current privacy protection systems (Tor, VPN) are used to anonymize web browsing history, then user privacy is improved, but user utility and personalized services are degraded
Solution Approach 1:
The patent segments browsing history into topic categories (e.g., news, entertainment, shopping) and applies different anonymization strategies to each topic. This allows selective preservation of useful browsing patterns while anonymizing sensitive areas, thereby maintaining personalized service quality in non-sensitive topics while protecting privacy in sensitive ones.
Solution Approach 2:
The system applies different levels of anonymization to different topics based on their sensitivity. High-sensitivity topics receive stronger anonymization while low-sensitivity topics maintain more original characteristics. This local differentiation resolves the contradiction by preserving service quality where possible while protecting privacy where necessary.
2Loss of information
If web browsing data is concealed to protect privacy, then user privacy is improved, but web services performance and site speed are degraded
Solution Approach 1:
The patent applies partial anonymization by adding synthetic browsing data only to topics where privacy is critical, rather than anonymizing all browsing history uniformly. This selective approach maintains adequate web service performance while providing privacy protection where most needed, avoiding the performance degradation that would result from complete anonymization.
3Loss of information
If browsing history is anonymized to protect privacy, then user privacy is improved, but predictability of online activity is hampered
Solution Approach 1:
The system changes the parameters of browsing history by adding synthetic data with controlled characteristics. The synthetic data is generated with topic distributions that match overall browsing patterns, maintaining statistical predictability at the aggregate level while obscuring individual user behavior. This resolves the contradiction by preserving predictability for service optimization while protecting individual privacy.
Data Source
AI summary
Systems and methods of privacy protection of a user may include compiling an actual number of links in a web history corresponding to each topic in a plurality of internet topics; compiling a topic probability distribution based on the web history; determining an additional number of links to be added to each topic in the plurality of internet topics; and modifying the topic probability distribution by selecting a set of links corresponding to the additional number of links for each topic in the plurality of internet topics.