Title
Real-time adaptive visual secret sharing with reversibility and high capacity
Abstract
Visual secret sharing is an efficient technique for the protection of real-time message transmissions. For the sake of security enhancement, the data hiding-based visual secret sharing (DH-VSS) methods are emerging and have gained considerable research attention in recent years. However, although most of the existing DH-VSSs are real-time algorithms, the computational complexity for a typical DH-VSS scheme still needs to be improved. Therefore, in this paper, we propose a more efficient real-time \((2,2)\) DH-VSS scheme based on the least-significant-bit (LSB) substitution technique with large embedding capacity. The original cover image is divided into eight bit planes in such a way that the secret messages are embedded in the 3-LSB bit planes to create two meaningful shadow images. This is an adaptive method since extra secret bits can be embedded into the fourth LSB bit plane of the first shadow image, depending on whether the currently processed pixel is in a smooth or complex block. The embedded secret messages can be losslessly extracted by the cooperation of both shadows; the original cover image can also be exactly restored. Experimental results show that the computational complexity of the proposed DH-VSS scheme is significantly lower than that of related state-of-the-art methods. Furthermore, its embedding capacity is greatly enhanced under less execution time. Therefore, the proposed scheme is computation efficient as well as practical so as to be quite suitable for diverse real-time applications.
Year
DOI
Venue
2019
10.1007/s11554-018-0813-9
Journal of Real-Time Image Processing
Keywords
Field
DocType
Visual secret sharing,Data hiding,Real time,Adaptive,Embedding capacity
Computer vision,Shadow,Bit plane,Embedding,Secret sharing,Computer science,Information hiding,Pixel,Artificial intelligence,Computer engineering,Computational complexity theory,Least significant bit
Journal
Volume
Issue
ISSN
16
4
1861-8219
Citations 
PageRank 
References 
2
0.37
16
Authors
3
Name
Order
Citations
PageRank
Ching-Chun Chang1266.30
Yanjun Liu2859.46
Kaimeng Chen320.37