CryptoCrypt

Streamlit
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Created by team team phoeniks on March 24, 2023

Introducing our innovative Streamlit application, which harnesses the power of OpenAI GPT-3 to generate multi-layer encryption and decryption codes for secure communication. This application is designed to help users easily encrypt and decrypt their messages using state-of-the-art encryption techniques, making it nearly impossible for unauthorized parties to access their sensitive information. To use this application, users can input their speech message through OpenAI Whisper, which transcribes the message accurately. The application then uses GPT-3 to generate a multi-layer encryption code, which can be customized by the user according to their specific requirements. Once the encryption code is generated, it is applied to the speech message, making it indecipherable to anyone without the decryption code. Users can choose from a variety of encryption algorithms and key lengths, and can also input their own unique encryption key for added security. The application also allows users to save and retrieve their encryption codes for future use, making it easy to communicate securely with their contacts. In addition to its powerful encryption capabilities, the application is also highly user-friendly, with a clean and intuitive interface that allows users to easily navigate and customize their encryption settings. With its cutting-edge technology and ease of use, this Streamlit application is the perfect solution for anyone looking to communicate securely and confidently in today's digital world.

Category tags:

Security, Communication, Code Generation

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GPT-3.5

"I enjoy the theory on data protection. I would recommend a last layer of security: when voice data is encrypted it can be transformed with unique noise. Therefore each data generation has a unique footprint indistinguishable from humans, although highly apparent to machines. If exact encrypted voice data is copied in pasted, the unique noise could be verified to correlate if this was stolen."

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Ervin Moore

PhD Computer Science Student