Coverless Information Hiding Method Based on the Chinese Mathematical Expression

Chen, Xianyi; Sun, Huiyu; Tobe, Yoshito; Zhou, Zhili; Sun, Xingming

doi:10.1007/978-3-319-27051-7_12

Cited by 70 publications

(74 citation statements)

References 19 publications

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“…A decentralized belief propagationbased method, PD-LBP, was proposed for multiagent task allocation in open and dynamic grid and cloud environments [38]. Chen et al proposed a coverless information hiding method using Chinese character technology with high efficiency [39]. Reference [40] proposed a self-adaptive artificial bee colony algorithm based on the global best candidate for global optimization to a real privacy clustering problem based on the K-means technique.…”

Section: Related Workmentioning

confidence: 99%

A Heuristic Model for Supporting Users’ Decision-Making in Privacy Disclosure for Recommendation

Zhang

Cui

et al. 2018

Security and Communication Networks

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Privacy issues have become a major concern in the web of resource sharing, and users often have difficulty managing their information disclosure in the context of high-quality experiences from social media and Internet of Things. Recent studies have shown that users' disclosure decisions may be influenced by heuristics from the crowds, leading to inconsistency in the disclosure volumes and reduction of the prediction accuracy. Therefore, an analysis of why this influence occurs and how to optimize the user experience is highly important. We propose a novel heuristic model that defines the data structures of items and participants in social media, utilizes a modified decision-tree classifier that can predict participants' disclosures, and puts forward a correlation analysis for detecting disclosure inconsistences. The heuristic model is applied to real-time dataset to evaluate the behavioral effects. Decision-tree classifier and correlation analysis indeed prove that some participants' behaviors in information disclosures became decreasingly correlated during item requesting. Participants can be "persuaded" to change their disclosure behaviors, and the users' answers to the mildly sensitive items tend to be more variable and less predictable. Using this approach, recommender systems in social media can thus know the users better and provide service with higher prediction accuracy.

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Section: Related Workmentioning

confidence: 99%

A Heuristic Model for Supporting Users’ Decision-Making in Privacy Disclosure for Recommendation

Zhang

Cui

et al. 2018

Security and Communication Networks

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“…Since the modern steganalyzers based on rich models [29], deep learnings [30], or combinations of these approaches [31] are now capable of detecting the presence of embedment of this type to a large extent, an ideal spatial domain data hiding method should be designed such that the cover and stego images are statistically indistinguishable. To avoid the statistical trace, some novel coverless data hiding methods based on based on scale invariant feature transform and bag of feature [32], or based on binary numbers and transformed by Chinese characters [33] are proposed. The compress domain data hiding method embeds data by modifying the compressed codes.…”

Section: Introductionmentioning

confidence: 99%

Efficient Data Hiding Based on Block Truncation Coding Using Pixel Pair Matching Technique

Hong

2018

Symmetry

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Abstract:In this paper, an efficient data hiding method that embeds data into absolute moment block truncation coding (AMBTC) codes is proposed. The AMBTC method represents image blocks by trios, and each trio consists of two quantization levels and an asymmetrically distributed bitmap. However, the asymmetric phenomena of bitmaps cause large degradation in image quality during data embedment. With the help of reference tables filled with symmetrical patterns, the proposed method exploits a symmetry adjustment model to modify the quantization levels in those smooth blocks to achieve the smallest distortion. If the block is complex, a lossless embedding method is performed to carry one additional bit. A sophisticated division switching mechanism is also proposed to modify a block from smooth to complex if the solution to the minimal distortion cannot be found. The payload can be adjusted by varying the threshold, or by embedding more bits into the quantization levels. The experiments indicate that the proposed work provides the best stego image quality under various payloads when comparing to the related prior works.

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“…At present, remarkable results have been achieved. Therefore, this paper proposes a parameter selection for a denoising algorithm based on the evaluation of no-reference image quality [10] and applies the no-reference image quality evaluation method to the image denoising algorithm [11][12][13], making it possible to adaptively select the optimal parameters. We embed it in the ROF model to experiment [14] in the search for the optimal parameters, while reducing the number of iterations of the algorithm.…”

Section: Introductionmentioning

confidence: 99%

A Cascaded Algorithm for Image Quality Assessment and Image Denoising Based on CNN for Image Security and Authorization

et al. 2018

Security and Communication Networks

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With the rapid development of Internet technology, images on the Internet are used in various aspects of people's lives. The security and authorization of images are strongly dependent on image quality. Some potential problems have also emerged, among which the quality assessment and denoising of images are particularly evident. This paper proposes a novel NR-IQA method based on the dual convolutional neural network structure, which combines saliency detection with the human visual system (HSV), used as a weighting function to reflect the important distortion caused by the local area. The model is trained using gray and color features in the HSV space. It is applied to the parameter selection of an image denoising algorithm. The experiment proves that our proposed method can accurately evaluate image quality in the process of denoising. It provides great help in parameter optimization iteration and improves the performance of the algorithm. Through experiments, we obtain both improved image quality and a reasonable result of subject assessment when the cascaded algorithm is applied in image security and authorization.

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Coverless Information Hiding Method Based on the Chinese Mathematical Expression

Cited by 70 publications

References 19 publications

A Heuristic Model for Supporting Users’ Decision-Making in Privacy Disclosure for Recommendation

A Heuristic Model for Supporting Users’ Decision-Making in Privacy Disclosure for Recommendation

Efficient Data Hiding Based on Block Truncation Coding Using Pixel Pair Matching Technique

A Cascaded Algorithm for Image Quality Assessment and Image Denoising Based on CNN for Image Security and Authorization

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