Captcha Recommender System

Prediction
Flowchart

Inspiration

The inspiration for a CAPTCHA recommendation system may come from the need to improve the user experience while still providing a secure way to differentiate between human and non-human users.

What it does

Our System will recommend such captcha which our not recognized by those bots. If our recommendation model predicts the captcha correctly then we will recommend the captcha which will be difficult to understand by our model.

How we built it

We collected the dataset and trained it using CNN algorithms , by using image processing our model is successfully predicting the captcha

Challenges we ran into

The hardest part in the whole project is the data. The captcha has so much additive noise which was hard to remove and to choose the algorithm which will be best fit for our model.

Accomplishments that we're proud of

Developing a system that is able to accurately recommend the most appropriate type of CAPTCHA for a given user based on their behavior and characteristics. Improving user experience by reducing the number of false positives and making the CAPTCHA process more user-friendly. Implementing a machine learning model that is able to learn and adapt over time, thus improving the accuracy of the CAPTCHA recommendations.

What we learned

Collaborating with a team Understanding the importance of data Learning about different deep learning frameworks Time management and organization Idea generation

What's next for Captcha Recommender System

Integration with other systems: The system could be integrated with other systems, such as user account management or fraud detection systems, to provide a more comprehensive security solution.