Local Personal Daemon for Privacy-Preserving Mobile Assistance
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Solution Overview
Problem
Monolithic online services that provide personalized assistance by gathering and monetizing vast amounts of personal data from users compromise security and privacy, as they share user information with third parties for revenue, leading to increased risks of exposure and abuse.
Innovation Solution
A personal daemon operating on a user's mobile computing device maintains and analyzes personal information locally, providing personalized assistance without sharing it with third parties except by explicit user direction, thus enhancing security and trust.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If monolithic online services gather and share vast amounts of personal data with third parties for monetization, then personalized assistance is provided, but security and privacy are compromised
Solution Approach 1:
The patent segments the centralized monolithic online service into distributed personal daemons running on individual user devices. Each daemon operates independently locally, processing personal data on the device rather than centralizing it in remote servers. This segmentation eliminates the single point of failure and reduces the attack surface for data breaches, while still providing personalized assistance through local intelligence.
Solution Approach 2:
The patent extracts the personal assistant functionality from the centralized online service and places it directly on the user's mobile device as a local daemon process. This extraction removes the need to share personal data with third-party servers for monetization purposes, as the intelligence resides locally. The daemon can provide personalized assistance using only local resources and user-approved data, eliminating the security and privacy risks associated with data sharing.
2Productivity
If personal information is shared with third parties for revenue generation, then service funding is enabled, but risk of data exposure and abuse increases
Solution Approach 1:
The personal daemon is designed to be self-sufficient, running locally on the user's device without requiring external servers for core functionality. It autonomously monitors user behavior, learns preferences, and provides personalized assistance using only local computational resources. This self-service capability eliminates the need to share data with third parties for funding, as the service sustains itself through local operation and can be supported by alternative models such as optional premium features or integrated app purchases.
3Object-affected harmful factors
If a personal daemon operates locally on the mobile device, then security and privacy are enhanced, but processing and memory resources are consumed
Solution Approach 1:
The personal daemon implements partial monitoring by selectively observing only the most relevant user behaviors and events rather than continuously analyzing all device activity. It uses event-driven architecture to activate processing only when specific trigger events occur, such as user interactions with particular apps or patterns matching learned preferences. This approach provides sufficient personalized assistance while significantly reducing the continuous processing and memory resource consumption compared to comprehensive monitoring.
Solution Approach 2:
The daemon dynamically adjusts its operational parameters based on device conditions, user preferences, and contextual factors. It can modify the intensity of monitoring, the frequency of analysis, and the level of detail in personalization based on available resources and user needs. This parameter adaptability allows the system to maintain effective security and privacy protection while optimizing resource usage to prevent excessive energy consumption and device performance degradation.
Data Source
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AI summary
Systems and methods of a personal daemon, executing as a background process on a mobile computing device, for providing personal assistant to an associated user is presented. While the personal daemon maintains personal information corresponding to the associated user, the personal daemon is configured to not share the personal information of the associated user with any other entity other than the associated user except under conditions of rules established by the associated user. The personal daemon monitors and analyzes the actions of the associated user to determine additional personal information of the associated user. Additionally, upon receiving one or more notices of events from a plurality of sensors associated with the mobile computing device, the personal daemon executes a personal assistance action on behalf of the associated user.