Dynamic Visual CAPTCHA Challenges for Bot Attack Mitigation
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Solution Overview
Problem
Conventional CAPTCHA challenges are vulnerable to attacks by software bots due to advancements in optical character recognition (OCR) technology, allowing malicious entities to easily solve challenges with low computational resources, leading to high-volume attacks.
Innovation Solution
Developing new CAPTCHA challenges that require significantly more computational resources to solve, such as launching an instance of an Internet browser or using specialized hardware like a graphics processing unit (GPU), making it difficult for software bots to carry out high-volume attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional CAPTCHA challenges are used, then ease of operation is maintained, but security against bot attacks deteriorates due to OCR technology advancements
Solution Approach 1:
The patent changes the fundamental parameter of CAPTCHA verification from simple text recognition to complex visual task completion. Instead of asking users to read distorted text, the system presents images with objects and asks users to perform visual tasks like identifying specific objects, counting them, or selecting them. This parameter change makes the challenge resistant to OCR technology while remaining solvable by humans.
Solution Approach 2:
The patent introduces an intermediary layer between the user and the verification system. Rather than directly presenting text to be read, the system uses images containing visual elements as an intermediary medium. The user interacts with these visual elements through a graphical interface, performing tasks that require visual processing rather than text recognition, thereby blocking automated OCR-based attacks.
2Reliability
If computational resources are increased to solve CAPTCHA, then security against bot attacks is improved, but productivity deteriorates due to resource-intensive requirements
Solution Approach 1:
The patent performs preliminary actions by pre-generating images containing various visual elements and pre-defining possible tasks. The system prepares a library of images with objects, scenes, and potential interaction points before the CAPTCHA challenge is initiated. When a challenge is presented, the system can quickly generate multiple possible tasks based on the pre-prepared visual content, enabling rapid verification without requiring heavy computational resources during the actual challenge resolution.
3Reliability
If CAPTCHA challenges require specialized hardware like GPU, then security against bot attacks is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service by allowing the user's own device to perform the visual processing tasks required for CAPTCHA verification. The system presents visual challenges that can be solved using the device's existing camera, display, and basic processing capabilities. Users take photographs with their device cameras, view images on their device screens, and interact with visual elements through touch interfaces. This approach leverages the device's inherent capabilities rather than requiring specialized external hardware.
Data Source
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AI summary
A technique for distinguishing between a human user and a software robot. The technique includes: receiving a first communication from a device different from the at least one computer; identifying, from the first communication, a request to access a web resource; transmitting software code and location information to the device, wherein the location information specifies a plurality of locations encoding a visual representation of a challenge text, and wherein the software code, when executed by an Internet browser, causes a plurality of graphical elements to be displayed at the plurality of locations in a webpage so that the webpage displays the challenge text; receiving a second communication from the device; identifying, from the second communication, a response text; and providing the device with access to the web resource based on a comparison between the challenge text and the response text.