Visual secret sharing is a secret sharing scheme where the decryption requires no computation. It has found many applications in online transaction security, privacy protection, and bar code security, etc. Recently, researches have indicated that combining visual secret sharing with the widely used Quick Response code may provide additional security mechanism to online transaction. However, current methods are either pixel-based, which requires high computational complexity or module-based, which sacrifices error correction capability of the original Quick Response code. Designing module-based visual secret sharing for the Quick Response code without sacrificing error correction capability is a challenging problem. To solve this problem, this paper proposes a (3, 3)-threshold visual secret sharing for Quick Response code scheme that fully explores the extra freedom provided by color visual secret sharing and color stacking. The binary secret Quick Response code is encoded into color shares. By stacking all the three shares, a binary color Quick Response code can be reconstructed. After the inherent pre-processing steps in a standard Quick Response code decoder, the original binary secret Quick Response code can be completely reconstructed. Thus, the original error correction capability of the Quick Response code is fully preserved. Theoretical analysis shows that the visual secret sharing for Quick Response code is secure under the condition that the computational device available to the attacker is limited to a decoder for standard Quick Response code. Experimental results verify that the secret Quick Response code cannot be reconstructed from just one share or any two shares. However, it can be 100% reconstructed once the three shares are stacked. The proposed visual secret sharing for Quick Response code is module-based, and it does not sacrifice the error correction capability. Furthermore, No extra pre-processing steps other than the standard Quick Response code decoder are required.
Color Visual Secret Sharing for QR Code with Perfect Module Reconstruction
