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A Local Differential Privacy Trajectory Protection Method Based on Temporal and Spatial Restrictions for Staying Detection

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Tsinghua Science and Technology 2024年第2期29卷 617-633页

作者： Weiqi Zhang Zhenzhen Xie Akshita Maradapu Vera Venkata Sai Qasim Zia Zaobo He guisheng yin College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China School of Computer Science and Technology Shandong UniversityQingdao 266237China Department of Computer Science Georgia State UniversityAtlantaGA 30303USA College of Information Science and Technology Jinan UniversityGuangzhou 510632China

The widespread availability of GPS has opened up a whole new market that provides a plethora of location-based services.Location-based social networks have become very popular as they provide end users like us with several such services utilizing GPS through our devices.However,when users utilize these services,they inevitably expose personal information such as their ID and sensitive location to the servers.Due to untrustworthy servers and malicious attackers with colossal background knowledge,users'personal information is at risk on these servers.Unfortunately,many privacy-preserving solutions for protecting trajectories have significantly decreased utility after deployment.We have come up with a new trajectory privacy protection solution that contraposes the area of interest for users.Firstly,Staying Points Detection Method based on Temporal-Spatial Restrictions(SPDM-TSR)is an interest area mining method based on temporal-spatial restrictions,which can clearly distinguish between staying and moving points.Additionally,our privacy protection mechanism focuses on the user's areas of interest rather than the entire trajectory.Furthermore,our proposed mechanism does not rely on third-party service providers and the attackers'background knowledge settings.We test our models on real datasets,and the results indicate that our proposed algorithm can provide a high standard privacy guarantee as well as data availability.

关键词： local-differential privacy stay points detection trajectory data areas of interest temporal-spatial clustering

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Threshold Filtering Semi-Supervised Learning Method for SAR Target Recognition

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Computers, Materials & Continua 2022年第10期73卷 465-476页

作者： Linshan Shen Ye Tian Liguo Zhang guisheng yin Tong Shuai Shuo Liang Zhuofei Wu Harbin Engineering University College of Computer Science and TechnologyHarbin150001China Xidian University Xi’an710000China The 54th Research Institute of CETC Shijiazhuang050000China University of Bologna Bologna40100Italy

The semi-supervised deep learning technology driven by a small part of labeled data and a large amount of unlabeled data has achieved excellent performance in the field of image processing.However,the existing semisupervised learning techniques are all carried out under the assumption that the labeled data and the unlabeled data are in the same distribution,and its performance is mainly due to the two being in the same distribution state.When there is out-of-class data in unlabeled data,its performance will be affected.In practical applications,it is difficult to ensure that unlabeled data does not contain out-of-category data,especially in the field of Synthetic Aperture Radar(SAR)image recognition.In order to solve the problem that the unlabeled data contains out-of-class data which affects the performance of the model,this paper proposes a semi-supervised learning method of threshold filtering.In the training process,through the two selections of data by the model,unlabeled data outside the category is filtered out to optimize the performance of the model.Experiments were conducted on the Moving and Stationary Target Acquisition and Recognition(MSTAR)dataset,and compared with existing several state-of-the-art semi-supervised classification approaches,the superiority of our method was confirmed,especially when the unlabeled data contained a large amount of out-of-category data.

关键词： Semi-supervised learning SAR target recognition threshold filtering out-of-class data

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SUDM-SP:A method for discovering trajectory similar users based on semantic privacy

高置信计算(英文)

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高置信计算(英文) 2023年第3期3卷 68-80页

作者： Weiqi Zhang guisheng yin Bingyi Xie College of Computer Science and Technology Harbin Engineering UniversityHarbin 150009China Department of Computer Science Georgia State UniversityGA 30303USA

With intelligent terminal devices’widespread adoption and global positioning systems’advancement,Location-based Social Networking Services(LbSNs)have gained considerable attention.The recommendation mechanism,which revolves around identifying similar users,holds significant importance in LbSNs.In order to enhance user experience,LbSNs heavily rely on accurate data.By mining and analyzing users who exhibit similar behavioral patterns to the target user,LbSNs can offer personalized services that cater to individual preferences.However,trajectory data,a form encompassing various sensitive attributes,pose privacy concerns.Unauthorized disclosure of users’precise trajectory information can have severe consequences,potentially impacting their daily lives.Thus,this paper proposes the Similar User Discovery Method based on Semantic Privacy(SUDM-SP)for trajectory analysis.The approach involves employing a model that generates noise trajectories,maximizing expected noise to preserve the privacy of the original trajectories.Similar users are then identified based on the published noise trajectory data.SUDM-SP consists of two key components.Firstly,a puppet noise location,exhibiting the highest semantic expectation with the original location,is generated to derive noisesuppressed trajectory data.Secondly,a mechanism based on semantic and geographical distance is employed to cluster highly similar users into communities,facilitating the discovery of noise trajectory similarity among users.Through trials conducted using real datasets,the effectiveness of SUDM-SP,as a recommendation service ensuring user privacy protection is substantiated.

关键词： Differential privacy LbSNs Semantic trajectory Recommendation

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DPTP-LICD:A differential privacy trajectory protection method based on latent interest community detection

高置信计算(英文)

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高置信计算(英文) 2023年第2期3卷 60-70页

作者： Weiqi Zhang guisheng yin Yuxin Dong Fukun Chen Qasim Zia College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China Department of Computer Science Georgia State UniversityAtlanta 30303USA

With the rapid development of high-speed mobile network technology and high-precision positioning technology,the trajectory information of mobile users has received extensive attention from academia and industry in the field of Location-based Social Networks.Researchers can mine users’trajectories in Location-based Social Networks to obtain sensitive information,such as friendship groups,activity patterns,and consumption habits.Therefore,mobile users’privacy and security issues have received growing attention in Location-based Social networks.It is crucial to strike a balance between privacy protection and data availability.This paper proposes a differential privacy trajectory protection method based on latent interest community detection(DPTP-LICD),ensuring strict privacy protection standards and user data availability.Firstly,based on the historical trajectory information of users,spatiotemporal constraint information is extracted to construct a potential community strength model for mobile users.Secondly,the latent interest community obtained from the analysis is used to identify preferred hot spots on the user’s trajectory,and their priorities are assigned based on a popularity model.A reasonable privacy budget is allocated to prevent excessive noise from being added and rendering the protected trajectory data unusable.Finally,to prevent privacy leakage,we add Laplace and exponential noise in generating preferred hot spots and recommending user interest points.Security and effectiveness analysis shows that our mechanism provides effective points of interest recommendations and protects users’privacy from disclosure.

关键词： Differential privacy Community detection Trajectory data Community of interest Recommendation

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Image-to-Image Style Transfer Based on the Ghost Module

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Computers, Materials & Continua 2021年第9期68卷 4051-4067页

作者： Yan Jiang Xinrui Jia Liguo Zhang Ye Yuan Lei Chen guisheng yin College of Computer Science and Technology Harbin Engineering UniversityHarbin150001China Heilongjiang Hengxun Technology Co. Ltd.Harbin150001China College of Engineering and Information Technology Georgia Southern UniversityStatesboro30458GAUSA

The technology for image-to-image style transfer(a prevalent image processing task)has developed rapidly.The purpose of style transfer is to extract a texture from the source image domain and transfer it to the target image domain using a deep neural network.However,the existing methods typically have a large computational cost.To achieve efficient style transfer,we introduce a novel Ghost module into the GANILLA architecture to produce more feature maps from cheap operations.Then we utilize an attention mechanism to transform images with various styles.We optimize the original generative adversarial network(GAN)by using more efficient calculation methods for image-to-illustration translation.The experimental results show that our proposed method is similar to human vision and still maintains the quality of the image.Moreover,our proposed method overcomes the high computational cost and high computational resource consumption for style transfer.By comparing the results of subjective and objective evaluation indicators,our proposed method has shown superior performance over existing methods.

关键词： Style transfer generative adversarial networks ghost module attention mechanism human visual habits

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An Incremental Graph Pattern Matching Based Dynamic Cold-Start Recommendation Method

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国际计算机前沿大会会议论文集 2016年第1期 48-50页

作者： Yanan Zhang guisheng yin Qiushi Zhao Software School Harbin University of Science and TechnologyHarbin150040China College of Computer Science and Technology Harbin Engineering UniversityHarbin150001China

In order to give accurate recommendations for cold-start user, researchers use social network to find similar users. These efforts assume that cold-start user’s social relationships are static. However social relationships of cold-start user may change as time pass by. In order to give accurate and timely in manner recommendations for cold-start user, it is need to update social relationship continuously. In this paper, we proposed an incremental graph pattern matching based dynamic cold-start recommendation method (IGPMDCR), which updates similar users for cold-start user based on topology of social network, and gives recommendations based on the latest similar users’ records. The experimental results show that, IGPMDCR could give accurate and timely in manner recommendations for cold-start user.

关键词： Dynamic cold-start recommendation Social network Incremental graph pattern matching Topology of social network

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Research on formalization of efficient query application problems with compound condition in software development

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The Journal of China Universities of Posts and Telecommunications 2017年第2期24卷 18-30页

作者： Yang Yuchen Wang Xiaofang yin guisheng College of Computer Science and Technology Harbin Engineering University National Engineering Laboratory for E-Government Modeling and Emulation Harbin Engineering University

This paper provides a formalized definition of the application problem of compound condition query （CCQ） and a formal method of applying requirements elicitation based on trace information space derived from trace algebra. With the formalized process of solving the application problem of CCQ, formal requirements specification of application of CCQ is given, a formalized and automatic mapping of the results of requirements elicitation to the formal requirements specification is performed, the software system model and the application code are developed. Through a sample application of comprehensive query on housing information, the feasibility of formalized and automatic software development for the application problem of CCQ is proved. The result has important implications for the other problems regarding formalization and automatic software development.

关键词： automatic programming formal specification requirements-based programming compound condition query

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A Random Anonymity Framework for Location Privacy

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Wuhan University Journal of Natural Sciences 2015年第6期20卷 521-529页

作者： YANG Songtao yin guisheng MA Chunguang College of Computer Science and Technology Harbin Engineering University College of Information and Electronic Technology Jiamusi University

Location k-anonymity techniques typically use anony- mous spatial region to ensure privacy. But these solutions are vul- nerable to multiple queries attacks and inference attacks. Failing to account for the obstacle in geographic space is a severe problem since adversaries will surely regard these constraints. A novel framework is proposed to enhance location-dependent queries, based on the theoretical work of k-anonymity and Voronoi diagrams, allows a user to express service requirement and privacy require- ment by specifying a region and an appropriate value ofk. A trusted anonymity server form a restricted set （k, r, s）, which is composed of a number of discrete points to meet the requirements for location k-anonymity and location /-diversity. The location-based services （LBS） server implements an efficient algorithm for continu- ous-region-query processing. Simulation results demonstrated that the framework is superior to previous works in terms of privacy. Moreover, discreteness and randomness of the anonymous set are conducive to resisting location tracking attacks.

关键词： data privacy location-based services（LBS） trusted third party k-anonymity

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基于字节码关键路径的智能合约漏洞检测

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哈尔滨工程大学学报 2022年第2期43卷 255-261页

作者：印桂生高乐庄园李俊哈尔滨工程大学计算机科学与技术学院黑龙江哈尔滨150001 国家工业信息安全发展研究中心北京100040

目前智能合约漏洞检测技术手段单一,多数方法只针对合约的源代码,鲜有面向智能合约其他类型的安全检测。本文在仅给定智能合约二进制代码的情况下,针对最高频的可重入漏洞、委托调用漏洞和时间戳依赖漏洞,设计并实现了一种基于关键路径... 详细信息

目前智能合约漏洞检测技术手段单一,多数方法只针对合约的源代码,鲜有面向智能合约其他类型的安全检测。本文在仅给定智能合约二进制代码的情况下,针对最高频的可重入漏洞、委托调用漏洞和时间戳依赖漏洞,设计并实现了一种基于关键路径的智能合约漏洞检测方法。基于合约字节码构建智能合约执行控制流图;根据智能合约漏洞特点定义关键指令及规则,生成关键路径;最后采用规则匹配实现漏洞检测。通过对以太坊网络上8000个智能合约进行实验测试,结果表明:该方法可有效检测上述3类漏洞,准确度高达93.75%。

关键词：区块链智能合约安全分析漏洞检测二进制代码字节码关键指令关键路径

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Ferroelectric phase transition in relaxor ferroelectric single crystals 0.76PMN-0.24PT

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Chinese Science Bulletin 2000年第15期45卷 1380-1385页

作者： XU guisheng LUO Haosu WANG Pingchu Ql Zhenyi yin Zhiwen Laboratory of Functional Inorganic Materials Shanghai Institue of CeramicsChinese Academy of SciencesShanghai 201800China Xiangtan Polytechnic University Xiangtan 411201China

The features of the single crystals 0.76PMN-0.24PT in dielectric, ferroelectric, pyroelectric properties and domain structures indicate that they are located between typical ferroelectrics and normal ones. The unpoled crystals present a transitional domain configuration between microdomains and typical macrodomains while the crystals on (001) cuts undergo field-induced phase transition under poling, showing two special temperature points Td and Tm during the succedent heating procedure. The dielectric constant starts to decrease drastically at Td during cooling, or the transformation from induced macrodomain to transitional domain takes place at Td during heating. Ferroelectric-paraelectric phase transition or depolarization continues within the whole temperature range of Td-Tm, where ferroelectric phase in the form of transitional macrodomains coexists with paraelectric phase. Then the crystals macroscopically transoform into paraelectric phase containing ferroelectric microdomains at a temperature

关键词： relaxor ferroelectrics single crystals ferroelectric phase transition domain structure PMNT.

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