检索结果-内蒙古大学图书馆

Aggregation-based dual heterogeneous task allocation in spatial crowdsourcing

Frontiers of Computer Science 2024年第6期18卷 215-227页

作者： Xiaochuan LIN Kaimin WEI Zhetao LI Jinpeng CHEN Tingrui PEI College of Information Science and Technology&Cyberspace Security Jinan UniversityGuangzhou 510632China National&Local Joint Engineering Research Center of Network Security Detection and Protection Technology Guangzhou 510632China Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou 510632China School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China

Spatial crowdsourcing(SC)is a popular data collection paradigm for numerous *** the increment of tasks and workers in SC,heterogeneity becomes an unavoidable difficulty in task *** researches only focus on the single-heterogeneous task ***,a variety of heterogeneous objects coexist in real-world SC *** dramatically expands the space for searching the optimal task allocation solution,affecting the quality and efficiency of data *** this paper,an aggregation-based dual heterogeneous task allocation algorithm is put *** investigates the impact of dual heterogeneous on the task allocation problem and seeks to maximize the quality of task completion and minimize the average travel *** problem is first proved to be ***,a task aggregation method based on locations and requirements is built to reduce task ***,a time-constrained shortest path planning is also developed to shorten the travel distance in a *** that,two evolutionary task allocation schemes are ***,extensive experiments are conducted based on real-world datasets in various *** with baseline algorithms,our proposed schemes enhance the quality of task completion by up to 25% and utilize 34% less average travel distance.

关键词： task allocation aggregation shortest path dual heterogeneous spatial crowdsourcing

来源：评论

学校读者我要写书评

暂无评论

Self-feedback LSTM regression model for real-time particle source apportionment

引用

Journal of Environmental Sciences 2022年第4期34卷 10-20页

作者： Wei Wang Weiman Xu Shuai Deng Yimeng Chai Ruoyu Ma Guoliang Shi Bo Xu Mei Li Yue Li Trusted AI System Laboratory College of Computer ScienceNankai UniversityTianjin 300350China KLMDASR Tianjin Key Laboratory of Network and Data Security TechnologyTianjin 300350China State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control College of Environmental Science and EngineeringNankai UniversityTianjin 300071China Institute of Mass Spectrometry and Atmospheric Environment Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution Jinan UniversityGuangzhou 510632China Guangdong-Hongkong-Macao Joint Laboratory of Collaborative Innovation for Environmental Quality Guangzhou 510632China

Atmospheric particulate matter pollution has attracted much wider attention *** recent years,the development of atmospheric particle collection techniques has put forwards new demands on the real-time source apportionments *** demands are summarized,in this paper,as how to set up new restraints in apportionment and how to develop a non-linear regression model to process complicated circumstances,such as the existence of secondary source and similar *** this study,we firstly analyze the possible and potential restraints in single particle source apportionment,then propose a novel three-step self-feedback long short-term memory(SF-LSTM)network for approximating the source *** proposed deep learning neural network includes three modules,as generation,scoring and refining,and regeneration *** from the scoring modules,SF-LSTM implants four loss functions representing four restraints to be followed in the apportionment,meanwhile,the regeneration module calculates the source contribution in a non-linear *** results show that the model outperforms the conventional regression methods in the overall performance of the four evaluation indicators(residual sum of squares,stability,sparsity,negativity)for the ***,in short time-resolution analyzing,SF-LSTM provides better results under the restraint of stability.

关键词： Time series Regression Self-feedback LSTM network Particle source apportionment

来源：评论

学校读者我要写书评

暂无评论

DBKEM-AACS: a distributed key escrow model in blockchain with anonymous authentication and committee selection

引用

Science China(Information Sciences) 2023年第3期66卷 289-290页

作者： Axin XIANG Hongfeng GAO Youliang TIAN Liang WAN College of Computer Science and Technology Guizhou University Institute of Cryptography and Data Security Guizhou University Network and Information Management Center Guizhou University State Key Laboratory of Public Big Data Guizhou University Institute of Computer Software and Theory Guizhou University

Dear editor, key security is of great practical significance and demand to guarantee the security of digital assets in the blockchain system. At present, users prefer to escrow their assets on centralized institutions, but this phenomenon has gone against the unique characteristics of decentralization and anonymity in the blockchain. Among them, the suspense incidents of assets lock or lost are enough to prove that the security of escrowed keys on the exchanges is questionable.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dynamic Detection of Malicious Code on Android Based on Improved Multi-feature Gaussian Kernel 15th

Dynamic Detection of Malicious Code on Android Based on Impr...

引用

15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019

作者： Yu, Qing Luo, Xixi Wang, Zuohua Tianjin Key Laboratory of Intelligence Computing and Network Security Tianjin University of Technology Tianjin300384 China China Everbright Bank Co. Ltd. Tianjin300384 China

ISBN: (纸本)9783030325909

In recent years, with the increasing demand for mobile Internet, smartphones represented by the Android system begin to play an increasingly important role in people’s daily life. Due to the payment and social functions of smartphones, users’ property safety and personal privacy are increasingly threatened by malicious mobile apps. Lured by great interests, malicious applications began to spread in the mobile platform, malicious code is escalating, Android-side security is facing great threats. Therefore, it is very important to study the detection of malicious code in Android. This paper studies and analyzes the status of Android malicious code detection. On the basis of dynamic detection, this paper presents a dynamic detection algorithm of multi-feature IGK. The algorithm optimizes feature selection and Gaussian kernel function and applies the improved algorithm to multi-feature training to improve the detection accuracy of malicious code. We track application system calls and system service calls while the system is running, extract features from system call sequences and system service calls. Then we use the improved weighted information gain method to select the features. Finally, in view of the deficiencies of the traditional Gaussian kernel function in recognition rate and processing time, an improved Gaussian kernel function is proposed for machine learning. We evaluated our approach with 800 benign applications and 1200 malicious applications. The experimental results show that by the above two improvements, the highest detection rate is 97.5%, better than the existing methods. © 2020, Springer Nature Switzerland AG.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

A Linked List Encryption Scheme for Image Steganography without Embedding

引用

Computer Modeling in Engineering & Sciences 2024年第10期141卷 331-352页

作者： Pengbiao Zhao Qi Zhong Jingxue Chen Xiaopei Wang Zhen Qin Erqiang Zhou Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu610054China Faculty of Data Science City University of MacaoMacao999078China Department of Computer Science and Engineering University of CaliforniaRiversideCA 92521USA

Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information *** enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover *** this paper,a novel encrypted communication scheme for image SWE is *** reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer *** employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be *** receiver can restore the secretmessage fromthe received image using only the list header position *** scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover *** boasts high concealment and security,along with a complete message restoration rate,making it resistant to ***,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of *** validate the proposed framework,practical tests and comparisons are conducted using multiple *** results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.

关键词： Steganography encryption steganography without embedding coverless steganography

来源：评论

学校读者我要写书评

暂无评论

Design and implementation of coronavirus vaccines information traceability system based on blockchain

Design and implementation of coronavirus vaccines informatio...

引用

2021 International Symposium on Artificial Intelligence and its Application on Media, ISAIAM 2021

作者： Nie, Peng Zhou, Xinxing Wang, Chong Zheng, Huilin Zeng, Yubing Nankai University College of Cyber Science Tianjin Key Laboratory of Network and Data Security Technology Tianjin300350 China Nankai University College of Computer Science Tianjin300350 China Nankai University College of Cyber Science Tianjin300350 China

ISBN: (纸本)9781665432603

At the moment of COVID-19's continuing popularity, vaccination has become a necessary measure to fight against the COVID-19 under the community of common destiny. In order to provide more reliable vaccines traceability information that will not be tampered with and improve the worldwide COVID-19 vaccination management system, we designed and implemented a COVID-19 vaccines information traceability system. The system has three major functions. Firstly, with the help of blockchain technology, the system provides reliable input and query of traceability information for the production and transportation of COVID-19 vaccines. Secondly, it provides the historical injection information of COVID-19 vaccines. Thirdly, it realizes the safe conversion from historical injection information to QR code. The COVID-19 vaccines information traceability system not only allows people to inquire absolutely true vaccines traceability information, but also provides a standardized management platform of the COVID-19 vaccines for citizens and governments all over the world. © 2021 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Cryptanalysis of novel extended multivariate public key cryptosystem with invertible cycle

引用

International Journal of network security 2018年第3期20卷 509-514页

作者： Lu, Gang Xue, Linyuan Nie, Xuyun Qin, Zhiguang School of Information and Software Engineering University of Electronic Science and Technology of China Section 2 North Jianshe Road Chengdu610054 China State Key Laboratory of Information Security Institute of Information Engineering China Network and Data Security Key Laboratory of Sichuan Province China

In 2016, Qiao et al. proposed a novel extended multivariate public key cryptosystem (EMC) to enhance the security of multivariate public key cryptosystem. They applied it on Matsumoto-Imai (MI) encryption scheme and claimed that the enhanced MI scheme can be secure against Linearization Equation (LE) attack. Through analysis, we found that the enhanced MI scheme satisfied Quadratization Equations (QE). After finding all the quadratization equations, we can recover the plaintext corresponding to a valid ciphertext of the enhanced MI scheme. © International Journal of network security.

关键词： Public key cryptography

来源：评论

学校读者我要写书评

暂无评论

Password Guessing via Neural Language Modeling 1

引用

2nd International Conference on Machine Learning for Cyber security, ML4CS 2019

作者： Li, Hang Chen, Mengqi Yan, Shengbo Jia, Chunfu Li, Zhaohui College of Artificial Intelligence Nankai University Tianjin300350 China College of Cyber Science Nankai University Tianjin300350 China Tianjin Key Laboratory of Network and Data Security Nankai University Tianjin300350 China

ISBN: (数字)9783030306199

ISBN: (纸本)9783030306182

Passwords are the major part of authentication in current social networks. The state-of-the-art password guessing approaches, such as Markov model and probabilistic context-free grammars (PCFG) model, assign a probability value to each password by a statistic approach without any parameters. These methods require large datasets to accurately estimate probability due to the law of large number. The neural network, approximating target probability distribution through iteratively training its parameters, was used to model passwords by some researches. However, since the network architectures they used are simple and straightforward, there are many ways to improve it. In this paper, we view password guessing as a language modeling task and introduce a deeper, more robust, and faster-converged model with several useful techniques to model passwords. This model shows great ability in modeling passwords while significantly outperforms state-of-the-art approaches. Inspired by the most advanced sequential model named Transformer, we use it to model passwords with bidirectional masked language model which is powerful but unlikely to provide normalized probability estimation. Then we distill Transformer model’s knowledge into our proposed model to further boost its performance. Comparing with the PCFG, Markov and previous neural network models, our models show remarkable improvement in both one-site tests and cross-site tests. Moreover, our models are robust to the password policy by controlling the entropy of output distribution. © 2019, Springer Nature Switzerland AG.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

A Secure and Lightweight Client-Side Deduplication Approach for Resisting Side Channel Attacks

A Secure and Lightweight Client-Side Deduplication Approach ...

引用

IEEE International Conference on Communications (ICC)

作者： Yuchen Chen Chunfu Jia Guanxiong Ha Xuan Shan Hang Chen The College of Cyber Science Nankai University Tianjin China Tianjin Key Laboratory of Network and Data Security Technology Tianjin China Key Laboratory of Data and Intelligent System Security (DISSec) Data Security Technology Tianjin China

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Client-side deduplication system is widely used in cloud storage systems to reduce storage and communication overhead by eliminating the storing and uploading of duplicate data. However, it is vulnerable to side channel attacks, where an adversary can infer the existence status of uploaded data based on deterministic relations in duplication check responses. To address this issue, Random Response (RARE) was proposed, which sends duplication check requests for two chunks simultaneously. Nevertheless, RARE has limitations in terms of communication efficiency and security. In this paper, we propose Random Zero-one Coding Response (RZCR) to overcome these limitations. RZCR achieves lightweight coding of multiple chunks using a novel linear mapping algorithm, allowing for a balance between security and performance through the adjustment of system parameters. Furthermore, we, for the first time, formally define a security game to model these side channel attacks in client-side deduplication systems and introduce a stronger threat model compared to RARE. security analysis demonstrates that RZCR effectively mitigates the risk of side channel attacks. We also implement a prototype of RZCR and evaluate its performance using large-scale real-world datasets (i.e., Enron Email and Fslhomes) as well as synthetic datasets. The results show that RZCR significantly reduces communication overhead compared to representative schemes.

关键词： Threat modeling Privacy data privacy Prototypes Side-channel attacks Resists Games

来源：评论

学校读者我要写书评

暂无评论

Attribute Propagation Enhanced Community Detection Model for Bitcoin De-anonymizing 3rd

Attribute Propagation Enhanced Community Detection Model for...

引用

3rd International Conference on Machine Learning for Cyber security, ML4CS 2020

作者： Wang, Jiming Xie, Xueshuo Fang, Yaozheng Lu, Ye Li, Tao Wang, Guiling College of Computer Science Nankai University Tianjin300350 China College of Cyber Science Nankai University Tianjin300350 China Tianjin Key Laboratory of Network and Data Security Technology Tianjin300350 China New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)9783030622220

Bitcoin is a kind of decentralized cryptocurrency on a peer-to-peer network. Anonymity makes Bitcoin widely used in online payment but it is a disadvantage for regulatory purposes. We aim to de-anonymize Bitcoin to assist regulation. Many previous studies have used heuristic clustering or machine learning to analyze historical transactions and identify user behaviors. However, the accuracy of user identification is not ideal. Heuristic clustering only uses the topological structure of the transaction graph and ignores many transaction information, and supervised machine learning methods are limited by the size of labeled datasets. To identify user behaviors, we propose a community detection model based on attribute propagation, combining the topological structure of the transaction graph and additional transaction information. We first parse the transaction data of public ledger and construct a bipartite graph to describe correlations between addresses and transactions. We also extract address attributes from historical transactions to construct an attributed graph with the previous bipartite graph. Then, we design an adaptive weighted attribute propagation algorithm named AWAP running on the attributed graph to classify bitcoin addresses, and further identify user behaviors. Extensive experiments highlight that the proposed detection model based on AWAP achieves 5% higher accuracy on average compared to state-of-the-art address classification methods in Bitcoin. AWAP also achieves 25% higher F-score on average compared to previous community detection algorithms on two datasets. © 2020, Springer Nature Switzerland AG.

关键词： Bitcoin

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：