Dynamic Object Sequence Verification for Bot Mitigation
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Solution Overview
Problem
Current verification methods are either easily recognizable by machines, reducing security, or difficult for humans to complete, leading to high failure rates and inadequate security against malicious cyber activity.
Innovation Solution
A verification process that generates a random sequence of objects, creates a verification image with these objects, and provides a prompt message instructing users to sequentially click on the objects in a specified order, with the message converted into a picture to enhance security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a simple verification code is used, then the verification process is easy for users to complete, but machines can quickly recognize it, lowering verification security
Solution Approach 1:
The verification code transitions from a static image to a dynamic video sequence with randomized objects appearing and disappearing. The objects are displayed for only a brief period (e.g., 2-5 seconds), creating a time-sensitive challenge that is easy for humans to perceive quickly but difficult for machines to process and recognize in real-time.
Solution Approach 2:
The verification code adds the time dimension to the traditional spatial arrangement of objects. Instead of just arranging objects in a static grid, the system sequences objects temporally with randomized appearances and disappearances, requiring users to remember both spatial positions and temporal order, significantly increasing machine recognition difficulty.
2Reliability
If a complex verification code is used, then verification security is improved, but it becomes difficult for humans to recognize, assuring a high rate of verification failure
Solution Approach 1:
The verification code is segmented into multiple discrete objects with clear visual boundaries and distinct characteristics. Each object is individually identifiable and separated in both space and time, allowing users to process them one at a time in sequence rather than attempting to recognize a complex unified pattern all at once.
Solution Approach 2:
The verification code utilizes distinct visual characteristics including color variations among objects to enhance recognizability. Objects are presented with clear color contrasts and visual differentiation, making them easily distinguishable from one another even when displayed briefly, thereby maintaining high user recognition rates while preserving security.
3Measurement precision
If a high resolution verification image matrix is used, then the verification image has good discrimination, but it is easily learned and recognized by machines, lowering verification security
Solution Approach 1:
The verification code employs periodic display of objects with randomized intervals between appearances. Objects appear and disappear in a time-based sequence rather than remaining statically visible, creating a dynamic pattern that maintains clear visual discrimination during the display period while preventing machines from easily learning and recognizing the pattern through static analysis.
4Reliability
If a low resolution verification image matrix is used, then machines have difficulty recognizing it, but the verification image has poor discrimination and is difficult for users to recognize, assuring a high rate of verification failure
Solution Approach 1:
The system uses dynamic temporal sequencing to compensate for reduced spatial resolution. Objects are displayed sequentially over time with clear visual distinction during their appearance window, allowing adequate discrimination for human users while the time-sensitive nature prevents machine recognition, achieving both security and usability without requiring high static resolution.
Data Source
AI summary
Machine-based verification is minimized by presenting a web page to a user that includes a number of objects in a verification image, and then instructing the user to click on the objects in the verification image in a particular order. The user selected order is then compared to a known correct order, and verification is complete when the user selected order matches the known correct order.