Yujie Bao, Pincheng Wang^*, Yuhang Li

Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 143-154, 2020, DOI:10.32604/jihpp.2020.09759 - 18 December 2020

Abstract When big trucks are running at urban road intersections, they are easy to interfere with other motor vehicles, and the turning big trucks are easy to have conflicts with non-motor vehicles and pedestrians, which will affect the safety of intersections. This paper first studied the intersection of trucks to the running trajectory, on this basis, through the establishment of mathematical model analysis of large truck steering conditions inside the wheel, and the influence of blind area to the driver. In the research of intersection safety design, the safety design is divided into three parts: Entrance… More >

Tianyu Wang, Yu Xue, Yan Zhao, Yuxiang Wang^*, Yan Zhang, Yuxiang He

Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 135-142, 2020, DOI:10.32604/jihpp.2020.010362 - 18 December 2020

Abstract In the field of data mining and machine learning, clustering is a typical issue which has been widely studied by many researchers, and lots of effective algorithms have been proposed, including K-means, fuzzy c-means (FCM) and DBSCAN. However, the traditional clustering methods are easily trapped into local optimum. Thus, many evolutionary-based clustering methods have been investigated. Considering the effectiveness of brain storm optimization (BSO) in increasing the diversity while the diversity optimization is performed, in this paper, we propose a new clustering model based on BSO to use the global ability of BSO. In our… More >

Ming Zhao^*, Tao Liu

Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 125-134, 2020, DOI:10.32604/jihpp.2020.010211 - 18 December 2020

Abstract The problem of low accuracy of POI (Points of Interest) recommendation in LBSN (Location-Based Social Networks) has not been effectively solved. In this paper, a POI recommendation algorithm based on nonconvex regularized tensor completion is proposed. The fourth-order tensor is constructed by using the current location category, the next location category, time and season, the regularizer is added to the objective function of tensor completion to prevent over-fitting and reduce the error of the model. The proximal algorithm is used to solve the objective function, and the adaptive momentum is introduced to improve the efficiency More >

Ru Jin^*, Xinlian Zhou, Yue Wang

Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 115-123, 2020, DOI:10.32604/jihpp.2020.010180 - 18 December 2020

Abstract In a wireless sensor network [1], the operation of a node depends on the battery power it carries. Because of the environmental reasons, the node cannot replace the battery. In order to improve the life cycle of the network, energy becomes one of the key problems in the design of the wireless sensor network (WSN) routing protocol [2]. This paper proposes a routing protocol ERGD based on the method of gradient descent that can minimizes the consumption of energy. Within the communication radius of the current node, the distance between the current node and the More >

Xiangwei Meng, Jianbo Xu^*, Xiaohe Wu, Zhechong Wang

Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 107-114, 2020, DOI:10.32604/jihpp.2020.09901 - 18 December 2020

Abstract Please WBANs are a sensor network for detection and collection of sensitive data to the human body, which is lightweight and mobile. WBANs transmit sensitive and significant messages through the public channel, which makes it easy for an attacker to eavesdrop and modify the messages, thus posing a severe threat to the security of the messages. Therefore, it is essential to put in place authentication and key agreement between different communication nodes in WBANs. In this paper, a lightweight and secure authenticated key agreement protocol in wireless body area networks is designed. It is More >

Bingtao Hu^*, Jinwei Wang

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 95-105, 2020, DOI:10.32604/jihpp.2020.010464 - 11 November 2020

Abstract With the development of computer graphics, realistic computer graphics (CG) have become more and more common in our field of vision. This rendered image is invisible to the naked eye. How to effectively identify CG and natural images (NI) has been become a new issue in the field of digital forensics. In recent years, a series of deep learning network frameworks have shown great advantages in the field of images, which provides a good choice for us to solve this problem. This paper aims to track the latest developments and applications of deep learning in More >

Xin Liu^*, Xiao Chen

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 87-94, 2020, DOI:10.32604/jihpp.2020.09839 - 11 November 2020

Abstract In recent years, with the rapid growth of generative adversarial networks (GANs), a photo-realistic face can be easily generated from a random vector. Moreover, the faces generated by advanced GANs are very realistic. It is reasonable to acknowledge that even a well-trained viewer has difficulties to distinguish artificial from real faces. Therefore, detecting the face generated by GANs is a necessary work. This paper mainly introduces some methods to detect GAN-generated fake faces, and analyzes the advantages and disadvantages of these models based on the network structure and evaluation indexes, and the results obtained in More >

Yan Zhou, Lili Pan^*, Rongyu Chen, Weizhi Shao

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 77-86, 2020, DOI:10.32604/jihpp.2020.010486 - 11 November 2020

Abstract In large-scale image retrieval, deep features extracted by Convolutional Neural Network (CNN) can effectively express more image information than those extracted by traditional manual methods. However, the deep feature dimensions obtained by Deep Convolutional Neural Network (DCNN) are too high and redundant, which leads to low retrieval efficiency. We propose a novel image retrieval method, which combines deep features selection with improved DCNN and hash transform based on high-dimension features reduction to gain lowdimension deep features and realizes efficient image retrieval. Firstly, the improved network is based on the existing deep model to build a… More >

Rongyu Chen, Lili Pan^*, Yan Zhou, Qianhui Lei

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 67-76, 2020, DOI:10.32604/jihpp.2020.010472 - 11 November 2020

Abstract With the rapid development of information technology, the speed and efficiency of image retrieval are increasingly required in many fields, and a compelling image retrieval method is critical for the development of information. Feature extraction based on deep learning has become dominant in image retrieval due to their discrimination more complete, information more complementary and higher precision. However, the high-dimension deep features extracted by CNNs (convolutional neural networks) limits the retrieval efficiency and makes it difficult to satisfy the requirements of existing image retrieval. To solving this problem, the high-dimension feature reduction technology is… More >

Dunhong Yao^1,2,3,*, Yu Chen⁴

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 59-65, 2020, DOI:10.32604/jihpp.2020.010223 - 11 November 2020

Abstract With the rapid development of the Internet, many enterprises have launched their network platforms. When users browse, search, and click the products of these platforms, most platforms will keep records of these network behaviors, these records are often heterogeneous, and it is called log data. To effectively to analyze and manage these heterogeneous log data, so that enterprises can grasp the behavior characteristics of their platform users in time, to realize targeted recommendation of users, increase the sales volume of enterprises’ products, and accelerate the development of enterprises. Firstly, we follow the process of big… More >