Dynamic Spam Call Billing System Using Probability-Based Risk Assessment
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Solution Overview
Problem
Existing methods for preventing spam calls, such as billing the sender a fixed amount, are ineffective as they can be manipulated, and the evaluation of calls is often made by receivers with low information literacy, while senders with high literacy can exploit these systems.
Innovation Solution
A spam call prevention apparatus that evaluates the risk of a call based on the sender's ID, history, and evaluation data, billing the sender a sum corresponding to the probability of being spam or fraudulent, and notifies the receiver to evaluate the call post-conversation, using a dynamic billing system to deter fraudulent calls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed billing amount (e.g., one dollar) is charged to spam call senders, then some deterrence is provided, but the billing amount is not effective enough to prevent spam calls
Solution Approach 1:
The billing amount is changed from a fixed value to a dynamic value that varies based on the spam probability assessment. The determination unit calculates different billing amounts corresponding to different probabilities of being evaluated as spam or fraud, making the billing system adaptive rather than static
Solution Approach 2:
The billing parameter is changed from a constant fixed amount to a variable amount based on the spam probability. The system determines the billing amount by referencing the calculated probability, thereby changing the parameter from static to dynamic to improve prevention effectiveness
2Measurement precision
If the receiver is asked to evaluate the call during the call, then immediate feedback is provided, but the receiver may be talked into pressing the wrong key due to manipulation
Solution Approach 1:
The evaluation request is sent after the call has ended, not during the call. This timing allows the receiver to evaluate the call without being influenced by the sender's manipulation tactics during the conversation, while still providing timely feedback for billing determination
Solution Approach 2:
The system converts the potential harm of receiver manipulation into benefit by implementing a post-call evaluation mechanism. The manipulation vulnerability is eliminated by removing the receiver from the evaluation decision during the call, and the evaluation is instead based on automated analysis of call characteristics
3Reliability
If senders with high information literacy are targeted, then more effective prevention can be achieved, but the system must account for sophisticated manipulation tactics
Solution Approach 1:
The system introduces an intermediary evaluation mechanism that assesses call characteristics and calculates spam probability without requiring the receiver to make subjective judgments. The determination unit acts as an intermediary that objectively evaluates the call based on predefined criteria and historical data
Solution Approach 2:
The system implements a feedback loop where evaluation results are returned to the sender after the call, providing information about the call's assessed probability of being spam or fraud. This feedback mechanism helps senders understand why their calls are being evaluated and adjusted their behavior accordingly
Data Source
AI summary
A spam call prevention apparatus 11 includes:a response unit 111 configured to convey, to a phone terminal of a sender of a call, a response that, in a case where the call from the sender is evaluated as a spam or a fraud by a receiver of the call, the sender is billed a sum of money corresponding to a probability of being evaluated as the spam or the fraud;a notification unit 112 configured to notify, when the sender has requested, in responding to the response, the call to the receiver, a phone terminal of the receiver of a request for returning an evaluation result of evaluating the call from the sender after the call between the sender and the receiver has ended; anda determination unit 114 configured to determine, when the call from the sender has been evaluated as the spam or the fraud in the evaluation result, the sum of money corresponding to the probability of being evaluated as the spam or the fraud, as a sum of billing.