Weiwei Jing

Heilongjiang University of Science and Technology

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Liusheng Huang

University of Science and Technology of China

Weijiang Xu

University of Science and Technology of China

Yifei Yao

Nanjing Tech University

Shaorong Wang

Huazhong University of Science and Technology

Xian Zheng

Shanghai Electric (China)

Mingming Shi

Shanghai Electric (China)

Yonglong Luo

Anhui Normal University

Jiaxuan Ren

Huazhong University of Science and Technology

Youhang Yang

Huazhong University of Science and Technology

Huiqin Guo

Chinese Academy of Medical Sciences & Peking Union Medical College

Cooperative Institutions

University of Science and Technology of China

Chinese Academy of Medical Sciences & Peking Union Medical College

Huazhong University of Science and Technology

Shanghai Electric (China)

Peking University

National Clinical Research

Sun Yat-sen University

Sichuan University

Xi'an Jiaotong University

Soochow University

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Privacy-preserving statistical quantitative rules mining

Scalable Information Systems (2007)

Weiwei Jing Liusheng Huang Yifei Yao Weijiang Xu

This paper considers the problem of mining Statistical Quantitative rules (SQ rules) without revealing the private information of parties who compute jointly and share distributed data. Based on several basic tools for Privacy-Preserving Data Mining (PPDM), including secure sum, secure mean and secure frequent itemsets, this paper presents two algorithms to accomplish privacy-preserving SQ rules mining over horizontally partitioned data. One is to securely compute confidence intervals for testing the significance of rules; the other is to securely discover SQ rules.

Private information retrieval

10.5555/1366804.1366892

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Privacy-preserving collision detection of two circles

Scalable Information Systems (2007)

Weijiang Xu Weiwei Jing Liusheng Huang Yifei Yao

The proliferation of the network has opened up great opportunities for cooperative computation. But privacy concerns often prevent different parties from sharing their data in order to do cooperative computation tasks. Secure multi-party computation deals with the privacy concern in cooperative computation while ensuring correctness of the computation and that no more information is revealed to a participant in the computation than can be inferred from that participant's input and output [10]. This paper addresses the problem of privacy preserving collision detection of two circles for the first time, which is an important problem in privacy preserving computational geometry. Four protocols are presented in this paper to solve the problem, and their correctness and security are also analyzed. The experimental results illustrate that our method for detecting collision of two moving circles is very effective.

10.5555/1366804.1366898

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Privacy-Preserving DBSCAN Clustering Over Vertically Partitioned Data

Weijiang Xu Liusheng Huang Yonglong Luo Yifei Yao Weiwei Jing

Data mining has been a popular research area for more than a decade because of its ability of efficiently extracting statistics and trends from large sets of data. However, in many applications, the data are originally collected at different sites owned by different users. The distributed data mining raises concerns about the privacy of individuals. This paper considers the problem of privacy preserving DBSCAN clustering over vertically partitioned data based on some results of SMC. Each site learns the final results about the clusters, but learns nothing about any other site 's data. An efficient secure intersection protocol is first proposed to implement privacy preserving DBSCAN clustering. The security and complexity of the protocols are also analyzed. The results show that the protocols preserve the privacy of the data and the time complexity as well as the communication complexity is acceptable.

DBSCAN

10.1109/mue.2007.174

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Privacy-preserving Inference of Regression Relationship

Journal of Chinese Computer Systems (2009)

Weiwei Jing

Inference of regression relationship is a fundamental content in statistical analysis.Its operational form is somehow too complicated to be computed efficiently.In order to solve multiple linear regression under secure two-party model,the secure protocols for maximum likelihood,sum of squared residuals and regression sum of square are proposed.According to their specialties of calculation,the simplification discipline of matrix continued product is summarized and the number of interactive time is reduced.At last,the applications for privacy-preserving predication detection are also discussed.

Statistical Inference

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An Efficient Scheme for Private Information Retrieval

Journal of Chinese Computer Systems (2007)

Weiwei Jing

The Private Information Retrieval protocol(PIR) is an important secure multi-party computation protocol.In PIR,a user can perform a query from a database without revealing his private information;meanwhile the privacy of the database will be protected,too.This paper proposes a new scheme in which we apply cryptographic technology on the auxiliary random servers protocol to solve the problem of PIR.This scheme is efficient in computational complexity and doesn't increase the cost of communication.It is very practical and can retrieve a block of bits.Detailed analysis of security,computational complexity and communicational complexity to the scheme is also given in this paper.

Private information retrieval

Communication Complexity

Oblivious transfer

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Privacy-Preserving Statistical Quantitative Rules Mining

Weiwei Jing Liusheng Huang Yifei Yao Weijiang Xu

Private information retrieval

Statistical Analysis

10.4108/infoscale.2007.209

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Harmonic coupling characteristic analysis based on HSS and comparison of harmonic source identification methods

Jiaxuan Ren Xinchen Wang Mingming Shi Weiwei Jing Xian Zheng

In order to meet the needs of energy conservation and environmental protection, the power system is gradually transforming to a new type of power system mainly based on new energy. And the following harmonic problems are becoming the focus of attention for experts and scholars in various countries. In this paper, a linear LCL filtering system and a nonlinear new energy grid-connected DC/DC converter are mathematically modeled using HSS theory, and the harmonic coupling characteristics of the models are analyzed with the harmonic transfer function matrix. Meanwhile, for the three data-driven algorithms used for harmonic source identification, this paper proposes a framework for harmonic source identification, and compares the various indicators of the three algorithms in the case of samples containing noise.

Harmonic Analysis

Harmonic

Identification

10.1117/12.3030215

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Protocols for Privacy-Preserving DBSCAN Clustering

International Journal of Security and Its Applications (2007)

Weijiang Xu Liusheng Huang Yonglong Luo Yifei Yao Weiwei Jing

Cooperative computation is one of the most important fields in computer science. In recent years, the development of networking increases the desirability of cooperative computation. But privacy concerns often prevent different parties from sharing their data. Secure multiparty computation techniques can dispel parties’ doubts about revealing privacy information in this situation. On the other hand, Data mining has been a popular research area for more than a decade. However, in many applications, the data are originally collected at different sites owned by different users. This paper considers the problem of privacy preserving DBSCAN clustering over vertically partitioned data based on some results of SMC. An efficient secure intersection protocol is first proposed. The security and complexity of the protocols are also analyzed. The results show that the protocols preserve the privacy of the data and the time complexity as well as the communication complexity is acceptable.

DBSCAN

Source

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Citations (7)

Dynamics Relation of Sight-seeing Agriculture, Agriculture Production and Fund Input——Make an Example of Qixianshan Rose Garden in Nanjing City

Weiwei Jing

This paper sets up nonlinear kinetics mode of sight-seeing agriculture, agriculture production and fund input and discusses the stability of the system, which includes sight-seeing agriculture and agriculture production. The result of study shows:The relation of sight-seeing agriculture, agriculture production and fund input is a very complicated nonlinear relation. Blind investment of agriculture production will make the sight-seeing agriculture scale small. While improving the use of agricultural resources of production will contribute to the development of sight-seeing agriculture. In case of using agricultural resources inefficiently, increasing the input of agricultural production blindly is unfavorable to the enlargement of agriculture production and the development of sight-seeing agriculture of this area. Only on the premise of improving the use efficiency of sight-seeing agricultural resources and reducing the average unit investment of agriculture production at the same time, it is possible to achieve the goal of optimize the agricultural production structure in this area and expand the scale of sight-seeing agriculture after increasing the agricultural production scale.

Sight

Investment

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Harmonic Coupling Characteristic Analysis of VSC under Single-phase Fault Conditions

Mingming Shi Weiwei Jing Xian Zheng Fu Hui Jiaxuan Ren

With the widespread application of voltage source converters (VSCs) in power systems, the harmonic issue is becoming increasingly prominent. Although this harmonic issue has been comprehensively and deeply studied in recent years, the harmonic coupling characteristics of VSC under power system fault conditions still remain and urgently need to be analyzed in-depth. Focusing on the topology of two-level VSC and respectively using the methods of Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT), this article analyzes the time-frequency characteristics of current waveforms flowing through the AC and DC ports of the VSC under power system fault conditions. And a wavelet neural network algorithm with particle swarm optimization (PSO-WNN) is proposed for quickly obtaining the harmonic content indexes of above current waveforms. Also, an overall framework is specially designed for programmable analysis of the harmonic coupling characteristics of VSCs operating in power system. In this article the results of a case study are given, and show that compared with the existing BP neural network methods, the proposed PSO-WNN algorithm has higher solving accuracy and faster convergence speed.

Harmonic Analysis

Harmonic

10.1109/iaecst60924.2023.10502558

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