Anqi Qiu^1,2, Xianyi Chen^1,2, Xingming Sun^1,2,*, Shuai Wang³, Guo Wei⁴

Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 49-60, 2019, DOI:10.32604/jihpp.2019.05881

Abstract A new information hiding technology named coverless information hiding is proposed. It uses original natural images as stego images to represent secret information. The focus of coverless image steganography method is how to represent image features and establish a map relationship between image feature and the secret information. In this paper, we use three kinds of features which are Local Binary Pattern (LBP), the mean value of pixels and the variance value of pixels. On this basis, we realize the transmission of secret information. Firstly, the hash sequence of the original cover image is obtained More >

Ruohan Meng^1,2, Zhili Zhou^1,2, Qi Cui^1,2, Xingming Sun^1,2,*, Chengsheng Yuan^1,2,3

Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 43-48, 2019, DOI:10.32604/jihpp.2019.05797

Abstract At present, the coverless information hiding has been developed. However, due to the limited mapping relationship between secret information and feature selection, it is challenging to further enhance the hiding capacity of coverless information hiding. At the same time, the steganography algorithm based on object detection only hides secret information in foreground objects, which contribute to the steganography capacity is reduced. Since object recognition contains multiple objects and location, secret information can be mapped to object categories, the relationship of location and so on. Therefore, this paper proposes a new steganography algorithm based on object More >

Pingshui Wang^1,*, Zecheng Wang¹, Qinjuan Ma¹

Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 35-42, 2019, DOI:10.32604/jihpp.2019.05942

Abstract The issue of privacy protection for mobile social networks is a frontier topic in the field of social network applications. The existing researches on user privacy protection in mobile social network mainly focus on privacy preserving data publishing and access control. There is little research on the association of user privacy information, so it is not easy to design personalized privacy protection strategy, but also increase the complexity of user privacy settings. Therefore, this paper concentrates on the association of user privacy information taking big data analysis tools, so as to provide data support for More >

Yongxiang Gu¹, Beijing Chen¹, Xu Cheng^1,*, Yifeng Zhang^2,3, Jingang Shi⁴

Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 23-33, 2019, DOI:10.32604/jihpp.2019.05938

Abstract Recently, deep learning has achieved great success in visual tracking. The goal of this paper is to review the state-of-the-art tracking methods based on deep learning. First, we categorize the existing deep learning based trackers into three classes according to network structure, network function and network training. For each categorize, we analyze papers in different categories. Then, we conduct extensive experiments to compare the representative methods on the popular OTB-100, TC-128 and VOT2015 benchmarks. Based on our observations. We conclude that: (1) The usage of the convolutional neural network (CNN) model could significantly improve the… More >

Yuxi Jia¹, Feng Li^1,2, Fei Wang^1,2,*, Yan Gui^1,2,3

Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 11-21, 2019, DOI:10.32604/jihpp.2019.05979

Abstract The Brain-Computer Interfaces (BCIs) had been proposed and used in therapeutics for decades. However, the need of time-consuming calibration phase and the lack of robustness, which are caused by little-labeled data, are restricting the advance and application of BCI, especially for the BCI based on motor imagery (MI). In this paper, we reviewed the recent development in the machine learning algorithm used in the MI-based BCI, which may provide potential solutions for addressing the issue. We classified these algorithms into two categories, namely, and enhancing the representation and expanding the training set. Specifically, these methods More >

Liang Bai¹, Yuzhen Liu¹, Xiaoliang Wang^1,*, Nick Patterson², F. Jiang²

Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 1-10, 2019, DOI:10.32604/jihpp.2019.06043

Abstract Internet of Things (IoT) is an emerging paradigm involving intelligent sensor networks that incorporates embedded technology for collecting data, communicating with external environments. Recently, cloud computing together with fog computing has become an important research area of the Internet of Things because of big data processing capabilities. It is a promising technology that utilizes cloud or fog computing / architecture to improve sensor computing, storage, and communication capabilities. However, recently it has been shown that this computing/architecture may be vulnerable to various attacks because of the openness nature of the wireless network. Therefore, it becomes… More >

Yong Hua¹,Bolun Chen^1,2,∗,Yan Yuan¹, Guochang Zhu¹, Fenfen Li¹

Journal on Internet of Things, Vol.1, No.2, pp. 77-88, 2019, DOI:10.32604/jiot.2019.05941

Abstract The problem of influence maximization in the social network G is to find k seed nodes with the maximum influence. The seed set S has a wider range of influence in the social network G than other same-size node sets. The influence of a node is usually established by using the IC model (Independent Cascade model) with a considerable amount of Monte Carlo simulations used to approximate the influence of the node. In addition, an approximate effect (1-1/e) is obtained, when the number of Monte Carlo simulations is 10000 and the probability of propagation is More >

Weiwei Liu^{1, *}, Yang Tang², Fei Yang², Jin Wang³

Journal on Internet of Things, Vol.1, No.2, pp. 71-76, 2019, DOI:10.32604/jiot.2019.05946

Abstract Carbon monoxide (CO) is harmful to our health, and even causes death. The main source of CO is automobile exhaust. Therefore, this article determines that CO is the emission factor, and finally the evaluation model is established. The model provides an important basis for the highway construction project design, traffic management, environmental pollution control, energy saving, environmental evaluation and so on. Compared with the traditional method that calculates the road traffic volume through the air emissions model, according to the total amount of air pollution control, this paper builds the emission diffusion model, which calculates More >

Xiaorong Zhao¹, Hongjin Zhu¹, Xiufang Qian^1,*, Chunpeng Ge²

Journal on Internet of Things, Vol.1, No.2, pp. 55-62, 2019, DOI:10.32604/jiot.2019.06315

Abstract In recent years, with the rapid development of China’s economy and the continuous improvement of people’s living standards, the number of motor vehicles and the number of drivers in the country have grown rapidly. Due to the increase in the number of vehicles and the number of motorists, the traffic accident rate is increasing, causing serious economic losses to society. According to the traffic accident statistics of the Ministry of Communications of China in 2009, more than 300,000 car accidents occurred in the year, most of which were caused by drunk driving. Therefore, this paper… More >

Yanpeng Wu¹, Xiaoqi Peng^1,*, Nur Mohammad²

Journal on Internet of Things, Vol.1, No.2, pp. 63-69, 2019, DOI:10.32604/jiot.2019.06111

Abstract The dosage of gold-antimony flotation process of 5 main drugs, including Copper Sulfate, Lead Nitrate, Yellow Medicine, No. 2 Oil, Black Medicine, with corresponding visual features of foam images, including Stability, Gray Scale, Mean R, Mean G, Mean B, Mean Average, Dimension and Degree Variance, were recorded. Parameter correlation analysis showed that the correlation among Copper Sulfate, Yellow Medicine, Black Medicine, as well as the correlation among Gray Scale, Mean R, Mean G, Mean B, is strong, and the correlation among Dimension, Gray Scale, Mean R, Mean G, Mean B, as well as the correlation More >