The captcha is a Turing test used to distinguish between machines and humans. It is considered as the verification code for the security on many websites. In recent years, deep learning has been widely used in the related field such as data analysis and computer vision. By applying deep learning method to captcha recognition, the vulnerabilities of the current captcha can be discovered, and the captcha can be further improved to reach a higher security level. This paper focuses on the captcha recognition based on deep learning, which is conducive to find the loopholes of current captcha to design more secure captcha. In this paper, the AlexNet neural network is analyzed in detail first, then the model is implemented to achieve captcha recognition for the simple and complex captcha data. The experiment results show that the recognition accuracy of the simple captcha and complex captcha data is close to 99%, and captcha recognition based on deep learning has a satisfied effect for recognition of captcha with different complexity.
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