AI Spam Detection With Task-Based Sender Responses
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Solution Overview
Problem
Existing communication technologies struggle to effectively deter spam senders, as the costs of time, money, and security disproportionately fall on the receiver, encouraging continued spamming.
Innovation Solution
A method and apparatus that utilize artificial intelligence to determine if a communication is spam, and generate a response requiring tasks to be completed by the sender, thereby imposing costs and deterring further spamming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional spam filtering techniques (black listing, gray listing, contextual filtering) are used, then spam messages can be filtered to some extent, but the costs of time, money, and security disproportionately fall on the receiver and do little to deter the sender from continuing to send spam
Solution Approach 1:
The patent inverts the traditional spam filtering approach by shifting the cost burden from the receiver to the sender. Instead of the receiver bearing the costs of time, money, and security for filtering spam, the system imposes costs on senders through automated responses that require task completion. This inversion fundamentally changes who bears the harm, thereby reducing the harmful effect on receivers while maintaining spam filtering effectiveness.
Solution Approach 2:
The patent implements a feedback mechanism where automated responses are sent back to spam senders requiring them to complete tasks. This feedback loop creates a deterrent effect by making senders bear the cost of their spamming actions, rather than allowing them to send spam without consequence. The feedback directly addresses the sender's behavior and modifies future spamming decisions.
2Reliability
If conventional spam filtering techniques are used, then some spam can be blocked, but these techniques do little to deter the sender from continuing to send spam messages
Solution Approach 1:
The patent reverses the traditional approach by making the sender bear the cost rather than the receiver. By requiring senders to complete tasks to send messages, the system inverts the cost structure and creates a deterrent that directly impacts sender behavior, thereby reducing spam sending frequency while maintaining blocking capability.
Solution Approach 2:
The automated response system provides immediate feedback to senders by requiring task completion before messages can be sent. This feedback mechanism creates a direct consequence for spamming behavior, making senders aware of the costs they must bear, which deters continued spamming and reduces overall spam sending frequency.
3Measurement precision
If artificial intelligence is used to determine spam, then accuracy in identifying spam can be improved, but system complexity increases
Solution Approach 1:
The patent introduces an automated response system as an intermediary between spam detection and traditional filtering methods. This intermediary layer handles the complex AI-based spam determination and translates it into actionable responses that impose costs on senders. The intermediary manages the complexity by encapsulating the AI decision-making process and presenting simplified outcomes, thereby improving detection accuracy without proportionally increasing overall system complexity.
Data Source
AI summary
Disclosed technology includes receiving a communication from a communication sending device. It is determined whether the received communication from the communication sending device is a spam communication. A response comprising one or more tasks is generated when the received communication is determined as spam communication. The generated response comprising one or more tasks is sent to the communication sending device.