scholarly journals Secret Image-Sharing Scheme Based on Multinode Authentication in the Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Lina Zhang ◽  
Tong Wang ◽  
Xiangqin Zheng ◽  
Junhan Yang ◽  
Liping Lv

Internet of things (IoT) has been developed and applied rapidly because of its huge commercial value in recent years. However, security problem has become a key factor restricting the development of IoT. The nodes of IoT are easy to be impersonated or replaced when attacked, which leads to the mistake of the uploaded data, the abnormal use of the application, and so on. Identifying the authenticity of the data submitted by the nodes is the top priority. We propose a scheme to verify the authenticity of multinode data. In this scheme, the authenticity of node data is checked through visual secret recovery and XOR operation together. The least significant bit (lsb) operation converts data from nodes into a bit, which improves the efficiency of data verification and reduces the risk of data leakage. This scheme achieves the purpose of verifying the data provided by the node, which avoids malicious attacks from illegal nodes. By analyzing the experiment result and comparing with other works, our scheme has the advantages of high verification efficiency, lightweight storage of nodes, and security verification.

2017 ◽  
Vol 22 (S1) ◽  
pp. 2293-2307 ◽  
Author(s):  
Li Li ◽  
M. Shamim Hossain ◽  
Ahmed A. Abd El-Latif ◽  
M. F. Alhamid

2016 ◽  
Vol 9 (17) ◽  
pp. 4075-4088 ◽  
Author(s):  
Zhi-Hui Wang ◽  
Ya-Feng Di ◽  
Jianjun Li ◽  
Chin-Chen Chang ◽  
Hui Liu

2009 ◽  
Vol 179 (19) ◽  
pp. 3247-3254 ◽  
Author(s):  
Du-Shiau Tsai ◽  
Gwoboa Horng ◽  
Tzung-Her Chen ◽  
Yao-Te Huang

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1452
Author(s):  
Yuyuan Sun ◽  
Yuliang Lu ◽  
Jinrui Chen ◽  
Weiming Zhang ◽  
Xuehu Yan

The (k,n)-threshold Secret Image Sharing scheme (SISS) is a solution to image protection. However, the shadow images generated by traditional SISS are noise-like, easily arousing deep suspicions, so that it is significant to generate meaningful shadow images. One solution is to embed the shadow images into meaningful natural images and visual quality should be considered first. Limited by embedding rate, the existing schemes have made concessions in size and visual quality of shadow images, and few of them take the ability of anti-steganalysis into consideration. In this paper, a meaningful SISS that is based on Natural Steganography (MSISS-NS) is proposed. The secret image is firstly divided into n small-sized shadow images with Chinese Reminder Theorem, which are then embedded into RAW images to simulate the images with higher ISO parameters with NS. In MSISS-NS, the visual quality of shadow images is improved significantly. Additionally, as the payload of cover images with NS is larger than the size of small-sized shadow images, the scheme performs well not only in visual camouflage, but also in other aspects, like lossless recovery, no pixel expansion, and resisting steganalysis.


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