Intelligent Call Protection via Cloud-Local Database Analysis
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Solution Overview
Problem
Current anti-harassment software for mobile terminals is inadequate in identifying and blocking unfamiliar or fraudulent phone numbers, leading to user disturbance from unwanted calls and potential missed important calls, as it relies on manual blacklisting and lacks real-time identification capabilities.
Innovation Solution
A system and method for intelligent call identification and blocking using a monitoring module, analyzing module, displaying module, and cloud/local number databases to analyze and mark incoming phone numbers, allowing for differential interception based on security levels and types, enabling synchronized analysis and user-defined interception operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual blacklisting is used to block harassing calls, then protection from known harassing numbers is improved, but the ability to identify and block unfamiliar fraudulent calls deteriorates
Solution Approach 1:
The system performs preliminary analysis of incoming calls by examining caller ID information, calling patterns, and time characteristics before the user decides whether to answer. This preliminary action enables the system to identify potential fraud attempts in advance, allowing users to make informed decisions about which calls to accept or reject.
Solution Approach 2:
The system provides feedback to users about the nature and risk level of incoming calls through display information showing analysis results. This feedback loop allows users to see why certain calls are flagged as suspicious, improving their ability to distinguish between important and fraudulent calls while maintaining control over call answering decisions.
2Object-affected harmful factors
If all incoming calls from unknown numbers are blocked, then harassment is reduced, but important calls may be missed
Solution Approach 1:
The system applies different analysis methods and protection levels to different types of incoming calls based on their specific characteristics. Rather than uniformly blocking all unknown numbers, the system analyzes each call's caller ID format, time patterns, and other local features to determine the appropriate level of scrutiny and whether to allow the call through to the user.
Solution Approach 2:
The system changes the parameters of call handling based on analysis results, such as modifying display information to highlight suspicious characteristics, adjusting ringing behavior for flagged numbers, or providing different interception options. These parameter changes allow flexible response to different call types without universally blocking important calls.
3Reliability
If comprehensive call analysis is performed to identify fraudulent calls, then call security is improved, but system complexity increases
Solution Approach 1:
The analysis system is segmented into distinct functional modules that handle different aspects of call analysis separately. Each module focuses on specific analysis tasks such as caller ID validation, time pattern recognition, or blacklist checking, making the overall complex system more manageable and maintainable while preserving comprehensive security analysis capabilities.
4Productivity
If real-time call identification is implemented, then protection responsiveness is improved, but processing time increases
Solution Approach 1:
The system performs partial analysis of incoming calls in real-time, focusing on the most critical security checks such as blacklist matching and obvious fraud pattern recognition. Less critical analysis tasks are performed asynchronously or with lower priority, allowing the system to provide timely protection responses without excessive processing delays that would slow down normal call handling.
Data Source
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AI summary
System and method for intelligent call blocking with block mode are provided. Said system comprises at least one of a local number database and a cloud number database, as well as a monitoring module used for monitoring the phone number of mobile terminal and preprocessing, an analyzing module used for analyzing obtained phone number by means of at least one of the local number database and the cloud number database and synthesizing marking information that is obtained by such analyzing, a displaying module used for displaying said marking information in a set area of said mobile terminal, a phone number marking module used for receiving marking information that is inputted by the user and is correlated with said phone number and delivering said marking information to the cloud number database; wherein, said local number database stores a part of or all of the phone numbers and corresponding marking information which have been verified and are stored in said cloud number database. The present invention can realize intelligent protection for the phone number, and significantly reduce harassment of rubbish phone calls to the user, without affecting the ordinary life of the user.