Name
Abstract | ||
|---|---|---|
In the traditional secret image sharing schemes, a dealer shares a secret image among a group of participants and an authorized subset of the participants with their shadow images can cooperate to retrieve the secret image. However, for a long live secret image, the intruders may have adequate time to gain enough amounts of the shadow images. In this paper, we propose a proactive secret image sharing scheme based on LISS. In the scheme, shadow images are updated periodically by the shareholders without changing the original secret image such that the previous shares are invalid and the secret image can be reconstructed only by the shadow images in the current period. The experimental results demonstrate that the proposed scheme can recover the secret image losslessly and the embedding capacity is acceptable. The quality of the shadow images may reduce after every refreshing operation. Nevertheless, the scheme is still applicable when the number of updating times is less than ten. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s11042-017-5412-4 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Proactive secret sharing, LISS, Distortion-free, Secret image sharing | Computer vision,Shadow,Embedding,Computer security,Computer science,Proactive secret sharing,Image sharing,Artificial intelligence,Distortion free | Journal |
Volume | Issue | ISSN |
77 | 15 | 1380-7501 |
Citations | PageRank | References |
1 | 0.35 | 32 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Guo | 1 | 52 | 9.47 |
| Huan Zhang | 2 | 104 | 20.09 |
| Zhangjie Fu | 3 | 405 | 19.78 |
| Bin Feng | 4 | 8 | 2.81 |
| Mingchu Li | 5 | 469 | 78.10 |