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Journal of Natural Gas Chemistry 2010年第6期19卷 611-616页

作者： Zhihua Gao Wei Huang lihua yin Kechang Xie Key Laboratory of Coal Science and Technology of Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan 030024 Shanxi China

Cu-Zn-Al slurry catalysts were prepared using a complete liquid-phase preparation technology under different heat treatment *** catalysts were characterized using X-ray diffraction,X-ray photoelectron spectroscope,and N2 *** application in the single-step synthesis of dimethyl ether from syngas was also *** results indicate that the type of heat treatment atmosphere has an influence on the Cu species and the Cu0/Cu＋ ratio on the catalyst ***,the final Cu/Zn ratio on the catalyst surface is mainly dependent on the composition and reaction environment of the catalyst and less on the type of heat treatment *** prepared catalysts can suppress sintering of active sites at high temperatures,and the type of heat treatment atmosphere mainly affects the capability of the catalyst for methanol *** catalysts perform best using N2 as the heat treatment atmosphere.

关键词： liquid-phase preparation technology slurry reactor dimethyl ether syngas heat treatment atmosphere

Threat-Based Declassification and Endorsement for Mobile Computing

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Chinese Journal of Electronics 2019年第5期28卷 1041-1052页

作者： yin lihua GUO Yunchuan ZHANG Huibing HUANG Wenting FANG Binxing Cyberspace Institute of Advanced Technology Guangzhou University The State Key Laboratory of Information Security Institute of Information Engineering CAS Guangxi Key Lab of Trusted Software Guilin University of Electronic Technology The National Computer Network Emergency Response Technical Team/Coordination Center of China

Declassification and endorsement can efficiently improve the usability of mobile ***, both declassify and endorse operations in practice are often ad-hoc and nondeterministic, thus, being insecure. From a new perspective of threat assessments,we propose the Threat-based typed security π-calculus(πTBTS) to model declassification and endorsement in mobile computing. Intuitively, when relaxing confidentiality policies and/or integrity policies, we respectively assess threats brought by performing these two relaxes. If these threats are acceptable, the declassification and/or endorsement operations are permitted; Otherwise, they are denied. The proposed assessments have explicit security conditions, results and less open parameters,so our approach solves the problem of the ad-hoc and nondeterministic semantics and builds a bridge between threat assessments and declassification/endorsement.

关键词： Declassification Endorsement Threat assessment Mobile computing π-Calculus

A game-theoretic approach for federated learning:A trade-off among privacy,accuracy and energy

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Digital Communications and Networks 2024年第2期10卷 389-403页

作者： lihua yin Sixin Lin Zhe Sun Ran Li Yuanyuan He Zhiqiang Hao Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan430074China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China

Benefiting from the development of Federated Learning(FL)and distributed communication systems,large-scale intelligent applications become *** devices not only provide adequate training data,but also cause privacy leakage and energy *** to optimize the energy consumption in distributed communication systems,while ensuring the privacy of users and model accuracy,has become an urgent *** this paper,we define the FL as a 3-layer architecture including users,agents and *** order to find a balance among model training accuracy,privacy-preserving effect,and energy consumption,we design the training process of FL as game *** use an extensive game tree to analyze the key elements that influence the players’decisions in the single game,and then find the incentive mechanism that meet the social norms through the repeated *** experimental results show that the Nash equilibrium we obtained satisfies the laws of reality,and the proposed incentive mechanism can also promote users to submit high-quality data in *** the multiple rounds of play,the incentive mechanism can help all players find the optimal strategies for energy,privacy,and accuracy of FL in distributed communication systems.

关键词： Federated learning Privacy preservation Energy optimization Game theory Distributed communication systems

Marginal Attacks of Generating Adversarial Examples for Spam Filtering

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Chinese Journal of Electronics 2021年第4期30卷 595-602页

作者： GU Zhaoquan XIE Yushun HU Weixiong yin lihua HAN Yi TIAN Zhihong Cyberspace Institute of Advanced Technology Guangzhou University

Digit information has been used in many areas and has been widely spread in the Internet era because of its convenience. However, many ill-disposed attackers, such as spammers take advantage of such convenience to send unsolicited information, such as advertisements, frauds, and pornographic messages to mislead users and this might cause severe *** many spam filters have been proposed in detecting spams, they are vulnerable and could be misled by some carefully crafted adversarial *** this paper, we propose the marginal attack methods of generating such adversarial examples to fool a naive Bayesian spam ***, we propose three methods to select sensitive words from a sentence and add them at the end of the sentence. Through extensive experiments, we show that the generated adversarial examples could largely reduce the filter's detecting accuracy, e.g. by adding only one word, the accuracy could be reduced from 93.6% to 55.8%. Furthermore, we evaluate the transferability of the generated adversarial examples against other traditional filters such as logic regression, decision tree and linear support vector machine based filters. The evaluation results show that these filters' accuracy is also reduced dramatically; especially,the decision tree based filter's accuracy drops from 100%to 1.51% by inserting only one word.

关键词： Spam filtering Marginal attack Adversarial example Machine learning

TPRPF:a preserving framework of privacy relations based on adversarial training for texts in big data

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Frontiers of Computer Science 2022年第4期16卷 239-241页

作者： Yuhan Chai Zhe Sun Jing Qiu lihua yin Zhihong Tian Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China

1Introduction Texts data are used to train deep learning models in cloud servers that have the strong computing power and large storage space,which can seriously endanger the user's ***,the attacker can use the intercepted text representations of text data of the primary learning tasks to train an adversarial classifier to infer private attributes or private information,such as gender,age of the user,and the relation between users.

关键词： text framework computing

A blockchain-based audit approach for encrypted data in federated learning

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Digital Communications and Networks 2022年第5期8卷 614-624页

作者： Zhe Sun Junping Wan lihua yin Zhiqiang Cao Tianjie Luo Bin Wang Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China College of Electrical Engineering Zhejiang UniversityHangzhou310058China

The development of data-driven artificial intelligence technology has given birth to a variety of big data *** has become an essential factor to improve these *** learning,a privacy-preserving machine learning method,is proposed to leverage data from different data *** is typically used in conjunction with cryptographic methods,in which data owners train the global model by sharing encrypted model ***,data encryption makes it difficult to identify the quality of these model *** data owners may launch attacks such as data poisoning and *** defend against such attacks,it is necessary to find an approach to audit encrypted model *** this paper,we propose a blockchain-based audit approach for encrypted *** uses a behavior chain to record the encrypted gradients from data owners,and an audit chain to evaluate the gradients’***,we propose a privacy-preserving homomorphic noise mechanism in which the noise of each gradient sums to zero after aggregation,ensuring the availability of aggregated *** addition,we design a joint audit algorithm that can locate malicious data owners without decrypting individual *** security analysis and experimental evaluation,we demonstrate that our approach can defend against malicious gradient attacks in federated learning.

关键词： Audit Data quality Blockchain Secure aggregation Federated learning

New-corrected functions of X-ray powder diffraction

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Chinese Science Bulletin 2009年第21期54卷 3940-3946页

作者： ZHANG QingLi LIU WenPeng DING lihua JIANG HaiHe yin ShaoTang Crystal Laboratory Anhui Institute of Optics and Fine Mechanics Chinese Academy of Sciences Hefei 230031 China

X-ray powder diffraction is an indispensable technique to study material structure, phase transition and so on. It is necessary for high quality diffraction data to get high-precision diffraction angle. This work proposed four corrected functions of X-ray powder diffraction angle. Two methods, linearization method and modified Levenberg-Marquardt iteration method, are given to solve the function parameters, and the modified Levenberg-Marquardt method has fast convergent speed and stable solution. Two methods can give closed parameters, including those of Lu, Liu, and Chu functions and polynomial. New-corrected functions were used to fit the diffraction angle error of the tetragonal rutile poly- crystalline TiO2 mixed with Gd0.45Y2.55Sc2Ga3O12 as a standard sample, and the computation result indicates that these functions can characterize the diffraction error very well. In some cases, the new-corrected functions can describe the diffraction angle error better than the reported corrected functions. At the same time, the lattice parameter of Gd0.45Y2.55Sc2Ga3O12 was computed with two methods. When the corrected function parameters and lattice parameters were solved by the least square method, the interaction of the function parameters and lattice parameters would result in great error. However, when the X-ray diffraction angles were corrected by corrected functions using a standard sample, the authentic lattice parameters can be obtained by the least square fitting.

关键词： X射线衍射校正功能 Marquardt 晶格参数最小二乘拟合功能参数标准样品计算结果

A Traceable Capability-based Access Control for IoT

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Computers, Materials & Continua 2022年第9期72卷 4967-4982页

作者： Chao Li Fan Li Cheng Huang lihua yin Tianjie Luo Bin Wang Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510700China PCL Research Center of Cyberspace Security Peng Cheng LaboratoryShenzhen518052China Department of Electrical and Computer Engineering University of WaterlooWaterlooN2L 3G1Canada College of Electrical Engineering Zhejiang UniversityHangzhou310058China

Delegation mechanism in Internet of Things(IoT)allows users to share some of their permissions with ***-based delegation solutions require that only the user who has registered in the cloud can be delegated *** is not convenient when a permission is delegated to a large number of temporarily ***,some works like CapBAC delegate permissions locally in an offline ***,this is difficult to revoke and modify the offline delegated *** this work,we propose a traceable capability-based access control approach(TCAC)that can revoke and modify permissions by tracking the trajectories of permissions *** define a time capability tree(TCT)that can automatically extract permissions trajectories,and we also design a new capability token to improve the permission verification,revocation and modification *** experiment results show that TCAC has less token verification and revocation/modification time than those of CapBAC and *** can discover 73.3%unvisited users in the case of delegating and accessing *** provides more information about the permissions delegation relationships,and opens up new possibilities to guarantee the global security in IoT delegation *** the best of our knowledge,TCAC is the first work to capture the unvisited permissions.

关键词： IoT access control permission delegation delegation trajectory capability revocation capability modification

SWRR:The Link Scheduling Algorithm Based on Weighted Round-Robin

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Computers, Materials & Continua 2019年第6期59卷 965-982页

作者： Tianbo Lu Ru Yan Chao Li lihua yin Hao Chen Xieyu Zou School of Software Engineering Beijing University of Posts and TelecommunicationsBeijing100876China Key Laboratory of Trustworthy Distributed Computing and Service(Beijing University of Posts and Telecommunications) Ministry of EducationBeijing100876China Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China Department Computer Science and Engineering The University of Texas at ArlingtonArlington76091USA

With the rapid development of the Internet,people pay more and more attention to the protection of *** second-generation onion routing system Tor is the most commonly used among anonymous communication systems,which can be used to protect user privacy *** recent years,Tor’s congestion problem has become the focus of attention,and it can affect Tor’s performance even user ***,we investigate the causes of Tor network congestion and summarize some link scheduling algorithms proposed in recent *** we propose the link scheduling algorithm SWRR based on WRR(Weighted Round Robin).In this process,we design multiple weight functions and compare the performance of these weight functions under different congestion conditions,and the appropriate weight function is selected to be used in our algorithms based on the experiment ***,we also compare the performance of SWRR with other link scheduling algorithms under different congestion conditions by experiments,and verify the effectiveness of the algorithm SWRR.

关键词： Weighted Round-Robin Tor congestion control link scheduling anonymous communication

Fed-DFE: A Decentralized Function Encryption-Based Privacy-Preserving Scheme for Federated Learning

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Computers, Materials & Continua 2022年第4期71卷 1867-1886页

作者： Zhe Sun Jiyuan Feng lihua yin Zixu Zhang Ran Li Yu Hu Chongning Na Cyberspace Institute of Advanced Technology(CIAT) Guangzhou UniversityGuangzhouChina School of Electrical and Data Engineering University of Technology SydneySydneyAustralia Zhejiang Lab HangzhouChina

Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw ***,the training mechanism for passing model parameters is still threatened by gradient inversion,inference attacks,*** a lightweight encryption overhead,function encryption is a viable secure aggregation technique in federation learning,which is often used in combination with differential *** function encryption in federal learning still has the following problems:a)Traditional function encryption usually requires a trust third party(TTP)to assign the *** a TTP colludes with a server,the security aggregation mechanism can be compromised.b)When using differential privacy in combination with function encryption,the evaluation metrics of incentive mechanisms in the traditional federal learning become *** this paper,we propose a hybrid privacy-preserving scheme for federated learning,called ***,we present a decentralized multi-client function encryption *** replaces the TTP in traditional function encryption with an interactive key generation algorithm,avoiding the problem of ***,an embedded incentive mechanism is designed for function *** models the real parameters in federated learning and finds a balance between privacy preservation and model ***,we implemented a prototype of Fed-DFE and evaluated the performance of decentralized function encryption *** experimental results demonstrate the effectiveness and efficiency of our scheme.

关键词： Decentralized function encryption incentive mechanism differential privacy federated learning