Google LLC (20240274134). CAPTCHA AUTOMATED ASSISTANT simplified abstract
Contents
CAPTCHA AUTOMATED ASSISTANT
Organization Name
Inventor(s)
Pedro Gonnet Anders of Zurich (CH)
CAPTCHA AUTOMATED ASSISTANT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240274134 titled 'CAPTCHA AUTOMATED ASSISTANT
The abstract describes a patent application for an adaptive and self-training CAPTCHA assistant that can distinguish between computer-generated communication and human-originated communication. This assistant uses a generative adversarial network with a generator to create synthetic answers and a discriminator to differentiate between human and synthetic answers.
- The CAPTCHA assistant is self-training and adaptive.
- It utilizes a generative adversarial network with a generator and discriminator.
- The discriminator is trained to distinguish between human and synthetic answers.
- The trained discriminator is used to identify potentially malicious remote entities.
- Remote entities are provided challenge phrases, and their answers are evaluated by the discriminator.
- The discriminator predicts whether the answer originated from a human or a computer-generated source.
Potential Applications: - Enhancing online security by preventing automated bots from accessing sensitive information. - Improving user verification processes on websites and applications. - Enhancing the effectiveness of CAPTCHA systems in differentiating between humans and bots.
Problems Solved: - Preventing automated bots from accessing secure systems. - Enhancing the reliability of online communication by verifying human users. - Improving the overall security of online platforms.
Benefits: - Increased security against malicious automated bots. - Enhanced user verification processes. - Improved protection of sensitive information online.
Commercial Applications: Title: "Enhancing Online Security with Adaptive CAPTCHA Assistant" This technology can be used in various industries such as e-commerce, banking, social media platforms, and online gaming to enhance security measures and protect user data from malicious activities.
Questions about the technology: 1. How does the self-training aspect of the CAPTCHA assistant improve its effectiveness over time? 2. What are the potential limitations of using a generative adversarial network for distinguishing between human and computer-generated communication?
Original Abstract Submitted
implementing and applying an adaptive and self-training captcha (“completely automated public turing test to tell computers and humans apart”) assistant that distinguishes between a computer-generated communication (e.g., speech and/or typed) and communication that originates from a human. the captcha assistant utilizes a generative adversarial network that is self-training and includes a generator to generate synthetic answers and a discriminator to distinguish between human answers and synthetic answers. the trained discriminator is applied to potentially malicious remote entities, which are provided challenge phrases. answers from the remote entities are provided to the discriminator to predict whether the answer originated from a human or was computer-generated.
