Abstract
Secret image sharing is a technique for sharing a secret message in such a fashion that stego image shadows are generated and distributed to individual participants. Without the complete set of shadows shared among all participants, the secret could not be deciphered. This technique may serve as a crucial means for protecting private data in massive Internet of things applications. This can be realized by distributing the stego image shadows to different devices on the Internet so that only the ones who are authorized to access these devices can extract the secret message. In this paper, we proposed a secret image sharing scheme based on a novel maze matrix. A pair of image shadows were produced by hiding secret data into two distinct cover images under the guidance of the maze matrix. A two-layered cheat detection mechanism was devised based on the special characteristics of the proposed maze matrix. In addition to the conventional joint cheating detection, the proposed scheme was able to identify the tampered shadow presented by a cheater without the information from other shadows. Furthermore, in order to improve time efficiency, we derived a pair of Lagrange polynomials to compute the exact pixel values of the shadow images instead of resorting to time-consuming and computationally expensive conventional searching strategies. Experimental results demonstrated the effectiveness and efficiency of the proposed secret sharing scheme and cheat detection mechanism.
Highlights
Massive Internet of things (Massive IoT) involves an immense number of devices that require to be connected reliably and gigantic loads of data that need to travel safely through the Internet
The core component of the proposed secret image sharing scheme is the maze matrix, which belongs to a group of reference matrices originating from steganographic methods
We give some experimental results to show the performance of the proposed secret image sharing scheme
Summary
Ching-Chun Chang 1 , Ji-Hwei Horng 2, * , Chia-Shou Shih 3 and Chin-Chen Chang 3,4. Department of Electronic Engineering, National Quemoy University, Kinmen 89250, Taiwan.
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