Data security and integrity plays an important part in any blockchain system. Nowadays, data tampering and related mishaps have been common which needs to be addressed.

What it does

To start with, we have used secret keys to generate a series of QR codes that is then embedded into an image and establish a unique modified identity for the image in order to detect its ill-usage.

How we built it

We generated QR-Code and resized it so that it can be embedded within the base image using NOT operation from the watermark. In order to embed multiple codes, we used focused to handle the LSB bit within the base image. Later the image was decoded from the watermark.

Challenges we ran into

It was difficult to define the encoding of QR code into the image multiple times. We used different algorithms to achieve it. Also, it was challenging to reduce the PSNR value. Moreover, we initially planned to develop a mock social media platform where users can upload images and claim if someone else has used his/her image and uploaded it.

Accomplishments that we're proud of

The project could successfully encode a series of QR codes into the image and we could reconstruct the original image from the encoded image. Also, we were able to MSE and PSNR values near to ideal.

What we learned

We learned various encoding and encrypting methods and also Steganography methods such as the Least Significant Bit method where we could optimize and embed the data within the image in the most optimized way. We also learnt about various attacks that could be performed on images and also learnt about multiple concepts on blockchain technology.

What's next for Enhanced Adaptive Watermarking System: EAWS

We wish to further take this idea and implement it for NFT and also for identifying Fake videos on social media platforms by tracking their source. Apart from that some of the other applications for which we would be extending our project is for extending it for copyright protection and Content data protection.

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