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Research on the Distribution Characteristics of Standardized Big data Resources Based on data Visualization——Taking Standardization Practice in Shandong Province as an Example

Research on the Distribution Characteristics of Standardized...

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IEEE International Conference on data Science in Cyberspace (DSC)

作者： Jinyang Sun Dongdong Peng Zhe Lu Mengran Zhai Ning Qi Yuanhua Qi SHANDONG SCICOM Information and Economy Research Institute Co. Ltd Jinan China Jinan Municipal Bureau of Big Data Jinan China Shandong Institute of Economy and Informatization Development Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology Shandong Academy of Sciences Jinan China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

Standardized big data, as a product of the combination of big data and standardization work, objectively reflects the status quo and trends of standardization work. An in-depth study of the distribution characteristics of standardized big data resources has important value for improving the efficiency of standardization. Therefore, this paper explores the characteristics of the distribution of standardization resources from the dimensions of spatial and temporal distribution, industry distribution, standard type distribution, and distribution of think tank experts through visual analysis methods. The study shows that: (1) the distribution of standardization resources in Shandong Province presents significant hierarchical and geographical characteristics; (2) from the viewpoint of the distribution of industry types and standard types, the distribution of standardization resources in Shandong Province presents a typical "long-tailed distribution"; (3) the distribution of think-tank experts presents obvious "agglomeration effect".

关键词： Industries Technological innovation Heavily-tailed distribution Animals Urban areas data visualization Forestry Big data Fisheries Standards

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Robust Secure Aggregation with Lightweight Verification for Federated Learning

Robust Secure Aggregation with Lightweight Verification for ...

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IEEE International Conference on Trust, security and Privacy in Computing and Communications (TrustCom)

作者： Chao Huang Yanqing Yao Xiaojun Zhang Da Teng Yingdong Wang Lei Zhou State Key Laboratory of Software Development Environment Beihang University Beijing China State Key Laboratory of Cryptology Beijing China Key Laboratory of Aerospace Network Security Ministry of Industry and Information Technology School of Cyber Science and Technology Beihang University Beijing China Beijing Key Laboratory of Network Technology Beihang University Beijing China School of Computer Science Southwest Petroleum University Chengdu China

Verifiable secure aggregation (VSA) is a critical procedure in federated learning (FL), where secure aggregation achieves local gradients aggregation while data confidentiality is preserved, and verifiability enables participants to verify the correctness of aggregated results returned by a central server (CS). Most of existing solutions for VSA employ cumbersome cryptographic primitives and techniques (e.g., homomorphic encryption, bilinear pairing, interactive proof systems), which impose high communication round complexity and computational costs on participants or CS. Besides, user dropouts occur commonly in cross-device FL as a result of unstable network connection, it is demanded to design particular mechanism to deal with such events. In this paper, we present a robust secure aggregation scheme with lightweight verification for FL, by utilizing Shamir’s secret sharing technique to design a random masking code to protect the confidentiality of local gradients and achieve resilience to possible user dropout. To support verifiability upon aggregation, we extend a multi-key homomorphic MAC to achieve verification over gradient vector space. We provide security analysis to show that our scheme can protect data confidentiality against collusion attacks, meanwhile ensure the verifiable results are unforgeable under the assumption pseudorandom functions exist. We implement our scheme to verify its correctness and feasibility, performance evaluation shows its advantages in terms of efficiency and functionality.

关键词： Performance evaluation data privacy Privacy Federated learning Computational efficiency Complexity theory Cryptography

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Graph-Based Terminal Ranking for Sparsification of Interference Coordination Parameters in Ultra-Dense Networks 10th

Graph-Based Terminal Ranking for Sparsification of Interfere...

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10th EAI International Conference on Mobile Networks and Management, MONAMI 2020

作者： Gou, Junxiang Wang, Lusheng Lin, Hai Peng, Min Ministry of Education School of Computer Science and Information Engineering Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Hefei230601 China Ministry of Education School of Cyber Science and Engineering Key Laboratory of Aerospace Information Security and Trusted Computing Wuhan University Wuhan430072 China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei230601 China

ISBN: (纸本)9783030640019

In the future mobile communication system, inter-cell interference becomes a serious problem due to the intensive deployment of cells and terminals. Traditional interference coordination schemes take long time for optimization in ultra-dense networks. Meanwhile, due to the increase of factors affecting communication and in order to better meet the communication needs of each terminal, an interference coordination scheme needs to fully consider multiple characteristic parameters of the terminal, which will further increase the scheme’s computational time. Therefore, we should compress all the data through sparsification of parameters before optimization. There are many terminal parameters, and the essence of sparsification of parameters is to rank terminals. In this paper, a graph-based terminal ranking scheme is designed. First, each terminal can be represented by its multiple parameters. Then, all terminals are used as the vertexes in the graph to form a complete weighted graph, and edge weights represent the degree of dissimilarity between terminals. A ranking of terminals is obtained by finding a minimum Hamiltonian path in the graph. Finally, the ranking of all parameter sequences is obtained according to terminals ranking, which makes the sparsity of all parameter sequences better. Simulation results show that the proposed scheme can accomplish sparsification of parameter sequences effectively, especially when the number of sequences increases. In addition, compared with the optimal coordination of traditional scheme, this scheme improves the fairness of the system while ensuring high system capacity, and dramatically reduces the computational time of interference coordination. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020.

关键词： Approximation algorithms

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MIMO Underwater Acoustic Communication in Shallow Water with Ice Cover

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China Ocean Engineering 2019年第2期33卷 237-244页

作者： HAN Xiao YIN Jing-wei LIU Bing GUO Long-xiang Acoustic Science and Technology Laboratory Harbin Engineering University Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University) Ministry of Industry and Information Technology College of Underwater Acoustic Engineering Harbin Engineering University

Although multiple-input multiple-output(MIMO) underwater acoustic(UWA) communication has been intensively investigated in the past years, existing works mainly focus on open-water environment. There is no work reporting MIMO acoustic communication in under-ice environment. This paper presents results from a recent MIMO acoustic communication experiment which was conducted in Bohai Gulf during winter. In this experiment, high frequency MIMO signals centered at 10 kHz were transmitted from a two-element source array to a four-element vertical receiving array at 1 km range. According to the received signal of different array elements, MIMO acoustic communication in under-ice environment suffers less effect from co-channel interference compared with that in open-water environment. In this paper, time reversal followed by a single channel decision feedback equalizer is used to process the experimental data. It is demonstrated that this simple receiver is capable of realizing robust performance using fewer hydrophones(i.e. 2) without the explicit use of complex co-channel interference cancelation algorithms, such as parallel interference cancelation or serial interference cancelation.

关键词： underwater acoustic communication MIMO shallow water ice cover

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Measurement-based analysis of characteristics of fast moving underwater acoustic communication channel

Measurement-based analysis of characteristics of fast moving...

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Frontiers of information technology (FIT)

作者： Yang Wang Honglu Yan Chenyu Pan Songzuo Liu State Key Laboratory of Acoustics Chinese Academy of Sciences Beijing China Maritime Environment Construction Office Beijing China Acoustic Science and Technology Laboratory Harbin Engineering University Harbin China Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University) Ministry of Industry and Information Technology Harbin China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798350345940

In the fast moving scene, the underwater acoustic communication (UWAC) channel has extremely complex time-varying characteristics. The lack of standardized channel model severely limits the development of mobile UWAC technology. In this paper, the channel time-varying impulse response (TVIR) is estimated based on the measured mobile UWAC data, and the correlation coefficient, spread function and envelope of the channel are analyzed. The analysis results show that the fast movement between the transmitter and the receiver will lead to serious deviation and amplitude variation of the multipath arrival time, which will cause large Doppler frequency offset and spread, and lead to the decline of channel correlation. In this paper, the statistical characteristics of the measured channel are analyzed, which is helpful to the development of mobile UWA channel model.

关键词： Time-frequency analysis Transmitters Channel estimation Receivers Acoustic measurements Channel models Velocity measurement

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blockchain-Based Efficient Public Integrity Auditing for Cloud Storage Against Malicious Auditors 16th

Blockchain-Based Efficient Public Integrity Auditing for Clo...

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16th International Conference on information security and Cryptology, Inscrypt 2020

作者： Li, Shanshan Xu, Chunxiang Zhang, Yuan Yang, Anjia Wen, Xinsheng Chen, Kefei School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China College of Cyber Security Jinan University Guangzhou China Department of Mathematics Hangzhou Normal University Hangzhou China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9783030718510

Public integrity auditing enables a user to delegate a third-party auditor (TPA) to periodically audit the integrity of the outsourced data. Whereas, the security of public auditing schemes relies on the trustworthiness of TPA: once TPA misbehaves, the data integrity auditing would be invalidated. In this paper, we propose a blockchain-based efficient public integrity auditing scheme to resist misbehaved TPA, where the user is required to check the behaviors of TPA in a much longer period compared with that of the data integrity auditing performed by TPA. To free users from heavy computation costs during the checking, our scheme uses two key techniques. We first design a smart contract to (1) enable TPA to record each auditing entry (which records the information about each auditing task) into the blockchain and (2) ensure the validity of each recorded entry. Then, we propose an auditing record chain built on the Ethereum blockchain to link all auditing entries corresponding to the same data in the chronological order. By doing so, the user only needs to check the last auditing entry generated by TPA to verify the trustworthiness of TPA (i.e., whether TPA has correctly performed the prescribed auditing tasks). Compared with existing schemes, where the user has to check multiple entries one by one, our scheme achieves the same security guarantee with constant and low costs in terms of communication and computation. © 2021, Springer Nature Switzerland AG.

关键词： Smart contract

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The Sensitive Properties of Hydrate Reservoirs Based on Seismic Stereoscopic Detection technology

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Acta Geologica Sinica(English Edition) 2020年第2期94卷 530-544页

作者： LIU Xueqin XING Lei QIN Zhiliang LIU Huaishan Acoustic Science and Technology Laboratory Harbin Engineering UniversityHarbin 150001China Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001China College of Underwater Acoustic Engineering.Harbin Engineering University Harbin 150001China Key Lab of Submarine Geosciences and Prospecting Techniques MOE and College of Marine GeosciencesOcean University of ChinaQingdao 266100China Evaluation and Detection Technology Laboratory of Marine Mineral Resources Qingdao 266100China National Laboratory for Marine Science and Technology Qingdao 266061China

Higher-precision determinations of hydrate reservoirs, hydrate saturation levels and storage estimations are important for guaranteeing the ability to continuously research, develop and utilize natural gas hydrate resources in China. With seismic stereoscopic detection technology, which fully combines the advantages of different seismic detection models, hydrate formation layers can be observed with multiangle, wide-azimuth, wide-band data with a high precision. This technique provides more reliable data for analyzing the distribution characteristics of gas hydrate reservoirs, establishing velocity models, and studying the hydrate-sensitive properties of petrophysical parameters;these data are of great significance for the exploration and development of natural gas hydrate resources. Based on a velocity model obtained from the analysis of horizontal streamer velocity data in the hydrate-bearing area of the Shenhu Sea, this paper uses three VCs(longitudinal spacing of 25 m) and four OBSs(transverse spacing of 200 m) to jointly detect seismic datasets consisting of wave points based on an inversion of traveltime imaging sections. Accordingly, by comparing the differences between the seismic phases in the original data and the forward-modeled seismic phases, multiangle coverage constraint corrections are applied to the initial velocity model, and the initial model is further optimized, thereby improving the imaging quality of the streamer data. Petrophysical elastic parameters are the physical parameters that are most directly and closely related to rock formations and reservoir physical properties. Based on the optimized velocity model, the rock elastic hydrate-sensitive parameters of the hydrate reservoirs in the study area are inverted, and the sensitivities of the petrophysical parameters to natural gas hydrates are investigated. According to an analysis of the inversion results obtained from these sensitive parameters, λρ, Vp and λμ are simultaneously controlled b

关键词： natural gas hydrate stereoscopic detection elastic modulus sensitive parameters

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Deep Learning Algorithms Design and Implementation Based on Differential Privacy 3rd

Deep Learning Algorithms Design and Implementation Based on ...

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

作者： Xu, Xuefeng Yao, Yanqing Cheng, Lei Key Laboratory of Aerospace Network Security Ministry of industry and information technology School of Cyberspace Science and Technology Beihang University Beijing100191 China State Key Laboratory of Software Development Environment Beihang University Beijing100191 China Beijing Key Laboratory of Network Technology Beihang University Beijing China Shenzhen Research Institute of Big Data Shenzhen518000 China

ISBN: (纸本)9783030622220

Deep learning models bear the risks of privacy leakage. Attackers can obtain sensitive information contained in training data with some techniques. However, existing differentially private methods such as Differential Privacy-Stochastic Gradient Descent (DP-SGD) and Differential Privacy-Generative Adversarial Network (DP-GAN) are not very efficient as they require to perform sampling multiple times. More importantly, DP-GAN algorithm need public data to set gradient clipping threshold. In this paper, we introduce our refined algorithms to tackle these problems. First, we employ random shuffling instead of random sampling to improve training efficiency. We also test Gaussian and Laplace Mechanisms for clipping gradients and injecting noise. Second, we employ zero Concentrated Differential Privacy (zCDP) to compute overall privacy budget. Finally, we adopt dynamical gradient clipping in DP-GAN algorithm. During each iteration, we random sample training examples and set the average gradients norm as the new threshold. This not only makes the algorithm more robust but also doesn’t increase the overall privacy budget. We experiment with our algorithms on MNIST data sets and demonstrate the accuracies. In our refined DP-SGD algorithm, we achieve test accuracy of 96.58%. In our refined DP-GAN algorithm, we adopt the synthetic data to train models and reach test accuracy of 91.64%. The results show that our approach ensures model usability and provides the capability of privacy protection. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Zero-Knowledge Proof-based Practical Federated Learning on blockchain

arXiv

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arXiv 2023年

作者： Xing, Zhibo Zhang, Zijian Li, Meng Liu, Jiamou Zhu, Liehuang Russello, Giovanni Asghar, Muhammad Rizwan The School of Computer Science The University of Auckland Auckland New Zealand The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China Southeast Institute of Information Technology Beijing Institute of Technology Fujian351100 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei230601 China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology China The Department of Computer Science University of Surrey The School of Computer Science The University of Auckland Auckland New Zealand

Since the concern of privacy leakage extremely discourages user participation in sharing data, federated learning has gradually become a promising technique for both academia and industry for achieving collaborative learning without leaking information about the local data. Unfortunately, most federated learning solutions cannot efficiently verify the execution of each participant's local machine learning model and protect the privacy of user data, simultaneously. In this article, we first propose a Zero-Knowledge Proof-based Federated Learning (ZKP-FL) scheme on blockchain. It leverages zero-knowledge proof for both the computation of local data and the aggregation of local model parameters, aiming to verify the computation process without requiring the plaintext of the local data. We further propose a Practical ZKP-FL (PZKP-FL) scheme to support fraction and non-linear operations. Specifically, we explore a Fraction-Integer mapping function, and use Taylor expansion to efficiently handle non-linear operations while maintaining the accuracy of the federated learning model. We also analyze the security of PZKP-FL. Performance analysis demonstrates that the whole running time of the PZKP-FL scheme is approximately less than one minute in parallel execution. Copyright © 2023, The Authors. All rights reserved.

关键词： blockchain

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Recommender Systems with Condensed Local Differential Privacy 3rd

Recommender Systems with Condensed Local Differential Privac...

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

作者： Liu, Ao Yao, Yanqing Cheng, Xianfu State Key Laboratory of Software Development Environment Beihang University Beijing100191 China Key Laboratory of Aerospace Network Security Ministry of Industry and Information Technology School of Cyberspace Science and Technology Beihang University Beijing100191 China Beijing Key Laboratory of Network Technology Beihang University Beijing100191 China

ISBN: (纸本)9783030622220

Recommender systems aim at predicting users’ future behaviors by learning the users’ personal information and historical behaviors. Unfortunately, training by the user’s raw data will inevitably cause the user’s private information to leak. Moreover, exiting privacy-preserving recommendation methods are based on matrix factorization with Local Differential Privacy (LDP). Because LDP performs poorly in small or multi-dimensional data sets, these methods do not work well with sparse or multi-dimensional features. Motivated by these questions, we propose a privacy-preserving recommendation model based on Deep neural networks and Factorization Machines (DeepFM), which can provide users with recommendations under the promise of protecting users’ privacy. In our recommendation model, each user randomly perturbs the calculated gradients to satisfy Condensed Local Differential Privacy (CLDP). The recommender system collects the perturbed gradients to train a recommendation model, which guarantees the safety of users’ private information and has excellent accuracy for the recommendation. Experiments on a real-world dataset show that the recommendation accuracy of our algorithm performs better than the existing methods. © 2020, Springer Nature Switzerland AG.

关键词： Deep neural networks

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