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13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020

作者： Wang, Linjie Tian, Youliang Xiong, Jinbo State Key Laboratory of Public Big Data College of Computer Science Technology Guizhou University Guiyang550025 China School of Data Science Tongren University Tongren554300 China College of Mathematics and Informatics Fujian Normal University Fuzhou350007 China

ISBN: (纸本)9781631902710

The authentication problem is one of the most significant challenges in the industrial Internet of Things control system applications. To authenticate the relationships between devices is an effective solution to tackle authentication issue. However, the previous studies of Internet of Things focused on connecting sensors and setting the sharing condition from either private or public in the sense that the relationship authentication issue between devices is not well solved. In this paper, we propose CDAA, a Cross-domain Dynamic Accumulator Authentication with a general undirected graph representing the relationship between devices needed authentication for industrial Internet of Things supporting trustworthiness cross-domain, cryptographic accumulator, and transferability. Specifically, a dynamically updatable cross-domain authentication scheme is proposed based on the cryptographic accumulator and a standard digital signature scheme as the underlay of the CDAA. Finally, we give the analysis and comparison and the results show that the proposed scheme can address the authentication issue. The effectiveness and feasibility of proposed scheme are presented and analyzed through a comparison with traditional systems in practical application. Copyright © 2020 EAI.

关键词： Internet of things

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NODLINK: An Online System for Fine-Grained APT Attack Detection and Investigation

arXiv

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arXiv 2023年

作者： Li, Shaofei Dong, Feng Xiao, Xusheng Wang, Haoyu Shao, Fei Chen, Jiedong Guo, Yao Chen, Xiangqun Li, Ding School of Computer Science Peking University China Arizona State University United States Case Western Reserve University United States Sangfor Technologies Inc. China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology China

Advanced Persistent Threats (APT) attacks have plagued modern enterprises, causing significant financial losses. To counter these attacks, researchers propose techniques that capture the complex and stealthy scenarios of APT attacks by using provenance graphs to model system entities and their dependencies. Particularly, to accelerate attack detection and reduce financial losses, online provenance-based detection systems that detect and investigate APT attacks under the constraints of timeliness and limited resources are in dire need. Unfortunately, existing online systems usually sacrifice detection granularity to reduce computational complexity and produce provenance graphs with more than 100,000 nodes, posing challenges for security admins to interpret the detection results. In this paper, we design and implement NODLINK, the first online detection system that maintains high detection accuracy without sacrificing detection granularity. Our insight is that the APT attack detection process in online provenance-based detection systems can be modeled as a Steiner Tree Problem (STP), which has efficient online approximation algorithms that recover concise attack-related provenance graphs with a theoretically bounded error. To utilize the frameworks of the STP approximation algorithm for APT attack detection, we propose a novel design of in-memory cache, an efficient attack screening method, and a new STP approximation algorithm that is more efficient than the conventional one in APT attack detection while maintaining the same complexity. We evaluate NODLINK in a production environment. The open-world experiment shows that NODLINK outperforms two state-of-the-art (SOTA) online provenance analysis systems by achieving magnitudes higher detection and investigation accuracy while having the same or higher throughput. Copyright © 2023, The Authors. All rights reserved.

关键词： Approximation algorithms

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Target-Mounted Intelligent Reflecting Surface for Joint Location and Orientation Estimation

arXiv

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arXiv 2023年

作者： Wang, Peilan Mei, Weidong Fang, Jun Zhang, Rui The National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore The The Chinese University of Hong Kong Shenzhen Shenzhen Research Institute of Big Data Shenzhen518172 China The Department of Electrical and Computer Engineering National Uiversity of Singapore Singapore117583 Singapore

Intelligent reflecting surface (IRS) has been widely recognized as an efficient technique to reconfigure the electromagnetic environment in favor of wireless communication performance. In this paper, we propose a new application of IRS for device-free target sensing via joint location and orientation estimation. In particular, different from the existing works that use IRS as an additional anchor node for localization/sensing, we consider mounting IRS on the sensing target, whereby estimating the IRS’s location and orientation as that of the target by leveraging IRS’s controllable signal reflection. To this end, we first propose a tensor-based method to acquire essential angle information between the IRS and the sensing transmitter as well as a set of distributed sensing receivers. Next, based on the estimated angle information, we formulate two optimization problems to estimate the location and orientation of the IRS/target, respectively, and obtain the locally optimal solutions to them by invoking two iterative algorithms, namely, gradient descent method and manifold optimization. In particular, we show that the orientation estimation problem admits a closed-form solution in a special case that usually holds in practice. Furthermore, theoretical analysis is conducted to draw essential insights into the proposed sensing system design and performance. Simulation results verify our theoretical analysis and demonstrate that the proposed methods can achieve high estimation accuracy which is close to the theoretical bound. Copyright © 2023, The Authors. All rights reserved.

关键词： Location

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Geospatial Disparities in Urban Electric Power Consumption and its Evolutionary Drivers in Countries Along the Belt and Road: Insights from Satellite Perspective

SSRN

引用

SSRN 2023年

作者： Zhong, Liang Yang, Peng Liu, Xiaosheng He, Yuanrong Lin, Yongpeng School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen361024 China School of Geodesy and Geomatics Wuhan University Wuhan430072 China School of Civil and Surveying&Mapping Engineering Jiangxi University of Science and Technology Ganzhou341000 China

Reducing the geographical disparities of urban electricity resources is a crucial foundation for maintaining sustainable development goals. This study developed a research framework utilizing multisource nighttime light data and geographical methods, aiming to systematically unveil geospatial differences in urban EPC and its evolutionary drivers in the Belt and Road (B&R) region from 2000 to 2019. The study demonstrated a significant geographic shift in the center of EPC in B&R cities, with mid-latitude cities emerging as the primary growth hubs. During the period from 2000 to 2019, the overall geospatial disparity of EPC in the B&R region gradually decreased, with inter-country differences being the primary contributing factor, accounting for approximately 70%. The multiscale EPC spatial gap changes reveal the existence of scale effects, which are caused by the different composition patterns of between-group and within-group gaps at corresponding scales. Affluence as the primary positive driver in reducing regional EPC disparities, followed by population size and energy dependence. Furthermore, an underlying U-shaped relationship between development disparities and affluence has been identified. These findings hold insightful implications for the sustainable development of urban energy, aiding the harmonized development of urban electric power resources amidst the enduring spatial variations. © 2023, The Authors. All rights reserved.

关键词： Population statistics

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Fine-grained Scheduling in FPGA-Based Convolutional Neural Networks 5

Fine-grained Scheduling in FPGA-Based Convolutional Neural N...

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5th IEEE International Conference on Cloud Computing and big data Analytics, ICCCBDA 2020

作者： Zhang, Wei Liao, Xiaofei Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan China

ISBN: (纸本)9781728160245

FPGA has been considered as a promising solution to accelerate Convolutional Neural Networks (CNNs) for its excellent performance in energy efficiency and programmability. However, prior designs are usually designed for inference only as designers can map pre-trained models to the hardware in a very efficient way. However, those approaches may not be suitable for training CNN models. In this paper, we propose FConv, in which the CPU and FPGA work together in a fine-grained manner. The FPGA accelerator in FConv uses one Winograd-based convolver, which reduces the design complexity and improves performance. We apply double-buffer for output routine to effectively overlap computation and data transfer. We also integrate multiple PEs to improve data parallelism. We propose our analytical model for prediction and use it as a guide in task scheduling. We find the upper limit of performance under the current design based on the analytical model. We evaluate our design on VGG-16 and Densnet-40 on ImageNet and CIFAR-10. We achieve 262.43 GOP/s on the VGG-16 model, which is 2.13 times of the performance compared to FFT-based implementation on the same platform. We also achieve at most 4 times+ performance improvement compared MKL with 20 threads running on 10 core Intel processors. © 2020 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Online Tensor Decomposition for Hyperspectral data Representation

Online Tensor Decomposition for Hyperspectral Data Represent...

引用

2021 China Automation Congress, CAC 2021

作者： He, Jinrong Shi, Yanxin Xie, Chengwang Bao, Zeyu Bai, Zongwen College of Mathematics and Computer Science Yan'an University Shaanxi China School of Computer and Information Engineering South China Normal University Shanwei China School of the Gifted Young University of Science and Technology of China Hefei China Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data Yan'an University Shaanxi China

ISBN: (纸本)9781665426473

Tensor is a natural representation of visual data, such as hyperspectral image data. Other than vector representation based feature extraction methods, tensor-based representation methods are more informative. Most existing data representation methods only work on vector spaces which are implemented by stacking the original tensor elements into a long vector. However, the vectorization will inevitably lost the underlying structural information and lead to high computational complexity. In order to reduce the memory requirements, we proposed an online tensor decomposition (OTD) method for hyperspectral image feature extraction. It does not require to load the whole tensor data set into main memory, and with the insertion of new tensor samples, it can update projection matrices incrementally, which is desirable for large data sets. In the experiments, the proposed method was applied into the task of apple hyperspectral data classification. The classification results confirm the effectiveness of online tensor decom-position method. © 2021 IEEE

关键词： Principal component analysis

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The Analysis of Commercial Pattern of Cloud Computing Platform 22

The Analysis of Commercial Pattern of Cloud Computing Platfo...

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3rd Asia Service sciences and Software Engineering Conference, ASSE 2022

作者： Liu, Haitao Qin, Zhi Ai, Xinxing Tu, Zhigang Zhang, Rongquan Guangxi Artificial Intelligence and Big Data Applying Institute Nanning530201 China Department of Human Resources and Social Security of Guangxi Zhuang Autonomous Region Nanning530022 China Guangxi Iron and Steel Group Co. Ltd. Fangchenggang538000 China Nanchang Randao Science and Technology Co. Ltd. Nanchang330038 China Guangxi University of Finance and Economics Nanning530004 China

ISBN: (纸本)9781450387453

For solving the problem which there have not suitable commercial pattern of cloud computing platform yet, a commercial pattern of cloud computing platform was proposed and constructed. The solving scheme are provided as follows. After explicitly demand surveyed, function analyzed and framework designed, an standard cloud computing platform with local characteristics and IoT think was constructed within 6 months successfully. After a period of time for operating and managing, for better operating the cloud computing platform, pursuing the continous income and excess profit, a creative and practical commercial pattern of cloud computing platform was presented and applied by this paper, that included in data Operation (DO) and Joint Credit Reference (JCR), which could solve the problem that the income of many cloud computing platform are not continuous. Then the performance of cloud computing platform was tentatively evaluated by Markov Random Field theory and Belief Propagation algorithm. Moreover, Cumulative Vote Scheme (CVS) which was also presented by this paper was used to analyze and evaluate the performance of commercial pattern of cloud computing platform. Three different random group samples were used to test and evaluate the performance of commercial pattern by independent practical experiments. Finally, the commercial pattern of cloud computing platform was proved to be very effectiveness by experiment results, and the performance of cloud computing platform was very robustness. © 2022 Association for Computing Machinery.

关键词： Cloud computing

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data Ownership Confirmation and Privacy-Free Search for Blockchain-Based Medical data Sharing 2nd

Data Ownership Confirmation and Privacy-Free Search for Bloc...

引用

2nd International Conference on Blockchain and Trustworthy Systems, Blocksys 2020

作者： Zha, Cong Yin, Hao Yin, Bo Network and Big Data Technology R&D Center The Department of Computer Science and Technology Tsinghua University Beijing100084 China The School of Computer Science Beijing Information Science and Technology University Beijing100084 China

ISBN: (纸本)9789811592126

With the development of data mining technology and the arrival of the era of big data, people can get more and more knowledge and information from the data. However, electronic medical data are stored in isolated data silos within each hospital due to the privacy and competition. Because of the complex interests of various groups, there is a lack of data flow between medical entities. On the one hand, this leads to difficulties for patients to obtain their own electronic medical data and to referral between different hospitals. On the other hand, it has led to serious lack of actual data for medical researchers. The realization of the determination of medical data ownership is the first condition for realizing medical data circulation. How to retrieve the required medical data while protecting privacy is the second problem to be solved. In this paper, we design the medical metadata as the smallest subunit of data ownership confirmation and propose a blockchain-based medical data sharing Framework MDSF, which can be used for electronic medical data ownership confirmation and data search while protecting patient privacy. We use the petri nets to verify the system and prove its reachability and boundedness, which means it can realize its designed function and operate safely. The system provides users with a convenient and safe way to obtain their past medical data, also enables research institutions engaged in medical data mining to easily search and obtain the actual medical data needed after desensitization. Thereby the circulation of medical data between different hospitals, individuals and research institutions is realized. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Hospitals

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The (r,δ)-Locality of Repeated-Root Cyclic Codes with Prime Power Lengths

arXiv

引用

arXiv 2023年

作者： Zhao, Wei Li, Weixian Yang, Shenghao Shum, Kenneth W. The School of Mathematics and Big Data Foshan University Guangdong528000 China The School of Mathematics South China University of Technology Guangdong510640 China The School of Mathematics and Statistics Zhaoqing University Guangdong526061 China The School of Science and Engineering The Chinese University of Hong Kong Guangdong Shenzhen518172 China

Locally repairable codes (LRCs) are designed for distributed storage systems to reduce the repair bandwidth and disk I/O complexity during the storage node repair process. A code with (r, δ)-locality (also called an (r, δ)-LRC) can simultaneously repair up to δ − 1 symbols in a codeword by accessing at most r other symbols in the codeword. In this paper, we propose a new method to calculate the (r, δ)-locality of cyclic codes. Initially, we give a description of the algebraic structure of repeated-root cyclic codes of prime power lengths. Using this result, we derive a formula of (r, δ)-locality of these cyclic codes for a wide range of δ values. Furthermore, we calculate the parameters of repeated-root cyclic codes of prime power lengths and obtain several infinite families of optimal cyclic (r, δ)-LRCs, which exhibit new parameters compared with existing research on optimal (r, δ)-LRCs with a cyclic structure. For the specific case of δ = 2, we have comprehensively identified all potential optimal cyclic (r, 2)-LRCs of prime power lengths. Copyright © 2023, The Authors. All rights reserved.

关键词： Multiprocessing systems

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A Solution for Cascade Hydropower Station Reservoirs Optimal Operation Based on Improved Bat Algorithm 6th

A Solution for Cascade Hydropower Station Reservoirs Optimal...

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6th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Dao, Thi-Kien Chang, Kuo-Chi Chu, Kai-Chun Nguyen, Thi-Thanh-Tan Ngo, Truong-Giang Nguyen, Trong-The Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Management Fujian University of Technology Fuzhou China Information Technology Faculty Electric Power University Hanoi Viet Nam Faculty of Computer Science and Engineering Thuyloi University Hanoi Viet Nam Haiphong University of Management and Technology Haiphong Viet Nam

ISBN: (纸本)9783030697167

This study suggests a solution to the optimal reservoir operation's typical nonlinear optimization problem by an improved Bat algorithm (IBA). The reservoir operations issue is modeled as the objective function according to the runoff data and comprehensive utilization requirements dealing with IBA’s optimization method. The IBA is implemented by introducing adaptive weight into the bat algorithm (BA) for updating mechanism. The bat's position is adjusted dynamically according to the actual situation to improve the bat's searching performance. The mechanism Tabu search (TS) diversity is also used to enhance the bat population diversity for preventing the situation that circuitous search does not leap out of the local optimum. The simulation results show that IBA can obtain a better reservoir operation scheme with higher operating efficiency than other algorithms, which offers a new way to maximize reservoir power generation operation. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Tabu search

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