Privacy Leak Detection via Linguistic Feature Analysis
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Solution Overview
Problem
Existing systems fail to effectively detect and prevent the inadvertent revelation of private information through textual input, which can lead to cyber attacks and compliance issues due to the use of innocuous words that may reveal sensitive information.
Innovation Solution
A method using a computing device to analyze textual input by generating combined queries with search engines, determining a confidence score based on the frequency of keyword and sensitive topic co-occurrence, and providing a user interface to highlight and replace potentially risky words with less revealing alternatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users write messages using natural language, then communication effectiveness is improved, but private information may be inadvertently revealed
Solution Approach 1:
The system performs preliminary detection of potentially revealing words in the message before it is sent. By analyzing the message content in advance and identifying words that could inadvertently reveal private information, the system allows users to review and modify the message to avoid information leakage while maintaining natural language communication.
2Object-affected harmful factors
If comprehensive detection of sensitive information is performed, then privacy protection is improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary component that acts as a detector between the user's message composition and the actual message sending. This intermediary detector analyzes the message content for potentially revealing words without requiring complex changes to the underlying communication system, thus providing comprehensive privacy protection while limiting the increase in system complexity.
3Measurement precision
If real-time analysis of message content is performed, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The system extracts and analyzes only the specific words in the message that have the potential to reveal private information, rather than performing comprehensive analysis on the entire message content. This selective extraction approach maintains high detection accuracy by focusing on critical elements while reducing the overall processing time required for real-time analysis.
Data Source
AI summary
Methods and systems are provided for detecting privacy leakage risks in text. One example method generally includes receiving, at a computing device from a client device, a keyword and generating, by the computing device, a combined query comprising the keyword and a sensitive topic query associated with a sensitive topic. The method further includes transmitting the keyword from the computing device to a search engine and transmitting the combined query from the computing device to the search engine. The method further includes receiving, at the computing device from the search engine, a number of search results for the keyword and receiving, at the computing device from the search engine, a number of search results for the combined query. The method further includes determining, by the computing device, a confidence score and transmitting the confidence score from the computing device to the client device.