Yabin Xu^1,2,*, Meishu Zhang², Xiaowei Xu³

Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 17-28, 2021, DOI:10.32604/jihpp.2021.017497 - 21 April 2021

Abstract In order to quickly and accurately find the implementer of the network crime, based on the user portrait technology, a rapid detection method for users with abnormal behaviorsis proposed. This method needs to construct the abnormal behavior rule base on various kinds of abnormal behaviors in advance, and construct the user portrait including basic attribute tags, behavior attribute tags and abnormal behavior similarity tagsfor network users who have abnormal behaviors. When a network crime occurs, firstly get the corresponding tag values in all user portraits according to the category of the network crime. Then, use More >

Yuanmin Shi^1,2, Siran Yin^1,2, Ze Chen^1,2, Leiming Yan^1,2,*

Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 9-16, 2021, DOI:10.32604/jihpp.2021.012193 - 21 April 2021

Abstract Privacy protection is a hot research topic in information security field. An improved XGBoost algorithm is proposed to protect the privacy in classification tasks. By combining with differential privacy protection, the XGBoost can improve the classification accuracy while protecting privacy information. When using CART regression tree to build a single decision tree, noise is added according to Laplace mechanism. Compared with random forest algorithm, this algorithm can reduce computation cost and prevent overfitting to a certain extent. The experimental results show that the proposed algorithm is more effective than other traditional algorithms while protecting the More >

Lei Zhao^*, Ming Zhao

Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 1-8, 2021, DOI:10.32604/jihpp.2021.010065 - 21 April 2021

Abstract Object detection has been studied for many years. The convolutional neural network has made great progress in the accuracy and speed of object detection. However, due to the low resolution of small objects and the representation of fuzzy features, one of the challenges now is how to effectively detect small objects in images. Existing target detectors for small objects: one is to use high-resolution images as input, the other is to increase the depth of the CNN network, but these two methods will undoubtedly increase the cost of calculation and time-consuming. In this paper, based… More >

Qianqian Li¹, Meng Li², Lei Guo^3,*, Zhen Zhang⁴

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 199-205, 2020, DOI:10.32604/jihpp.2020.016299 - 07 January 2021

Abstract On-site programming big data refers to the massive data generated in the process of software development with the characteristics of real-time, complexity and high-difficulty for processing. Therefore, data cleaning is essential for on-site programming big data. Duplicate data detection is an important step in data cleaning, which can save storage resources and enhance data consistency. Due to the insufficiency in traditional Sorted Neighborhood Method (SNM) and the difficulty of high-dimensional data detection, an optimized algorithm based on random forests with the dynamic and adaptive window size is proposed. The efficiency of the algorithm can be More >

Xingxing Cao¹, Liming Jiang^1,*, Xiaoliang Wang¹, Frank Jiang²

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 187-197, 2020, DOI:10.32604/jihpp.2020.016243 - 07 January 2021

Abstract Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods, the movement characteristics of trajectory data cannot be well expressed, which in turn affects the accuracy of the prediction results. First, a new trajectory data expression method by associating the movement behavior information is given. The pre-association method is used to model the movement behavior information according to the individual movement behavior features and the group movement behavior features extracted from the trajectory sequence and the region. The movement behavior features based on pre-association More >

Siran Yin^1,2, Leiming Yan^1,2,*, Yuanmin Shi^1,2, Yaoyang Hou^1,2, Yunhong Zhang^1,2

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 175-185, 2020, DOI:10.32604/jihpp.2020.010780 - 07 January 2021

Abstract Deep learning based on neural networks has made new progress in a wide variety of domain, however, it is lack of protection for sensitive information. The large amount of data used for training is easy to cause leakage of private information, thus the attacker can easily restore input through the representation of latent natural language. The privacy preserving deep learning aims to solve the above problems. In this paper, first, we introduce how to reduce training samples in order to reduce the amount of sensitive information, and then describe how to unbiasedly represent the data More >

Dongfang Yu, Jinwei Wang^*

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 165-174, 2020, DOI:10.32604/jihpp.2020.010466 - 07 January 2021

Abstract Chemical spectral analysis is contemporarily undergoing a revolution and drawing much attention of scientists owing to machine learning algorithms, in particular convolutional networks. Hence, this paper outlines the major machine learning and especially deep learning methods contributed to interpret chemical images, and overviews the current application, development and breakthrough in different spectral characterization. Brief categorization of reviewed literatures is provided for studies per application apparatus: X-Ray spectra, UV-Vis-IR spectra, Micro-scope, Raman spectra, Photoluminescence spectrum. End with the overview of existing circumstances in this research area, we provide unique insight and promising directions for the chemical More >

Peizhu Gong, Jin Liu^*, Shiqi Lv

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 155-163, 2020, DOI:10.32604/jihpp.2020.010453 - 07 January 2021

Abstract Image denoising is often used as a preprocessing step in computer vision tasks, which can help improve the accuracy of image processing models. Due to the imperfection of imaging systems, transmission media and recording equipment, digital images are often contaminated with various noises during their formation, which troubles the visual effects and even hinders people’s normal recognition. The pollution of noise directly affects the processing of image edge detection, feature extraction, pattern recognition, etc., making it difficult for people to break through the bottleneck by modifying the model. Many traditional filtering methods have shown poor… More >

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 >