Steganalysis of QR Code Using Deep Fractal Network

Because of its greater data capacity and improved damage resistance, the quick response code (QR) has emerged as the most popular barcode. When scanning data forms, barcode scanners may quickly and simply extract information from the QR code. However, in actual QR apps, certain private information stored directly in QR codes is not safe. To encode a secret QR code into separate shares, a visual secret sharing system is provided. In contrast to other methods, the shares in the proposed scheme are legitimate QR codes that can be read by a current QR code reader using a special method, increasing the number of suspicious attackers. The eligible shares are XORed in order to recover the secret message as well. Using smartphones or other QR scanning devices, this operation can be completed with ease. Contribution work includes developing the best partitioning strategies and utilising hashing methods to compare the original message with the shared message.