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

作者： Chen, Zhenwei Zhang, Yinghui Han, Gang He, Jiangyong Guo, Rui Zheng, Dong School of Cyberspace Security Xi’an University of Posts and Telecommunications Xi’an710121 China National Engineering Laboratory for Wireless Security Xi’an University of Posts and Telecommunications Xi’an710121 China Westone Cryptologic Research Center Beijing100070 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783030622220

Machine learning is more closely linked to data privacy and has obtained rapid development in recent years. As for data privacy, searchable encryption (SE) is widely used as a ciphertext search technology, protecting the privacy of users. However, existing schemes usually support single keyword search, so the remote cloud server (CS) may return some irrelevant results. To address this problem, we propose a server-aided public key encryption scheme with multi-keyword search (SA-PEMKS) scheme. The scheme allows a data user to conduct multiple keyword search in a single search query. Security and performance analysis show that the SA-PEMKS scheme is secure and efficient. © 2020, Springer Nature Switzerland AG.

关键词： data privacy

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Landscape of global urban environmental resistome and its association with local socioeconomic and medical status

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Science China(Life Sciences) 2024年第6期67卷 1292-1301页

作者： Jun Wu Yige Hu Michael H Perlin David Danko Jun Lu Manuela Oliveira Johannes Werner Maria M Zambrano Maria A Sierra Olayinka O Osuolale Paweł Łabaj Nicolás Rascovan Nur Hazlin Hazrin-Chong Soojin Jang Haruo Suzuki Marina Nieto-Caballero Bharath Prithiviraj Patrick K H Lee Agnieszka Chmielarczyk Anna Różańska Yongxiang Zhao Lan Wang Christopher E Mason Tieliu Shi Center for Bioinformatics and Computational Biology and the Institute of Biomedical SciencesSchool of Life SciencesEast China Normal UniversityShanghai 200241China Department of Biology Program on Disease EvolutionUniversity of LouisvilleLouisville 40292USA Weill Cornell Medicine New York 10065USA The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine New York 10065USA Department of Pulmonary Medicine Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200025China i3S-Instituto de Investiga玢o e Inova玢o em Saúde Universidade do PortoPorto 4050-290Portugal Ipatimup-Instituto de Patologia e Imunologia Molecular da Universidade do Porto Porto 4200-465Portugal Departamento de Biologia Faculdade de CiênciasUniversidade do PortoPorto 4050-290Portugal High Performance and Cloud Computing Group Zentrum für Datenverarbeitung(ZDV)Eberhard Karls University of TübingenW鋍hterstra遝7672074TübingenGermany Corporación Corpogen Research Center Bogotá110311Colombia Applied Environmental Metagenomics and Infectious Diseases Research(AEMIDR) Department of Biological SciencesElizade UniversityIlara-Mokin 340271Nigeria Maopolska Centre of Biotechnology Jagiellonian UniversityKraków 30-005Poland Aix-Marseille Université Mediterranean Institute of OceanologyUniversitéde ToulonCNRSIRDUM 110Marseille 83041France Department of Biological Sciences and Biotechnology Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangor Institut Pasteur Korea Seoul 13488Republic of Korea Faculty of Environment and Information Studies Keio UniversityFujisawaKanagawa 252-0882Japan University of Colorado at Boulder CivilEnvironmental and Architectural DepartmentBoulder 80303USA Brooklyn College of the City University of New York Brooklyn 11210USA School of Energy and Environment City University of Hong KongHong Kong 999077China Department of Microbiology Faculty of MedicineJagiellonian UniversityKraków 30-005Poland Biological Targeting Diagnosis and The

Antimicrobial resistance(AMR)poses a critical threat to global health and development,with environmental factors—particularly in urban areas—contributing significantly to the spread of antibiotic resistance genes(ARGs).However,most research to date has been conducted at a local level,leaving significant gaps in our understanding of the global status of antibiotic resistance in urban *** address this issue,we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples,which were collected by the Meta SUB International Consortium involving diverse urban environments in 60 cities of 27 countries,utilizing a deep-learning based *** findings demonstrated the strong geographical specificity of urban environmental resistome,and their correlation with various local socioeconomic and medical *** also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters(BGCs)across different countries,and discovered that the urban environment represents a rich source of novel *** study provides a comprehensive overview of the global urban environmental resistome,and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.

关键词： urban environment metagenome antibiotic resistance resistance diversity biosynthetic gene clusters

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Tracing the Local Void and its substructure with MeerKAT

Tracing the Local Void and its substructure with MeerKAT

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URSI Atlantic Radio Science Conference (URSI AT-RASC)

作者： Sushma Kurapati Renée C. Kraan-Korteweg D.J. Pisano Hao Chen Sambatriniaina H. A. Rajohnson Nadia Steyn Bradley Frank Paolo Serra Sharmila Goedhart Fernando Camilo Department of Astronomy University of Cape Town Private Bag X3 Rondebosch South Africa Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou China International Centre for Radio Astronomy Research The University of Western Australia 35 Stirling Highway Australia UK Astronomy Technology Centre Royal Observatory Edinburgh Blackford Hill Edinburgh UK South African Radio Astronomy Observatory 2 Fir Street Observatory South Africa The Inter-University Institute for Data Intensive Astronomy University of Cape Town Rondebosch South Africa Via della Scienza 5 INAF - Osservatorio Astronomico di Cagliari Selargius CA Italy

ISBN: (数字)9789463968102

ISBN: (纸本)9798350360257

The Local Void is the nearest large void. Nevertheless its properties are extremely difficult to observe since a major part of the Void is located behind the Galactic bulge. Here, we use Hi $21 \mathrm{~cm}$ emission observations extracted from the SARAO MeerKAT Galactic Plane Survey (SMGPS) to study the Local Void and its surroundings over the Galactic longitude range $329^{\circ}\lt \ell\lt 55^{\circ}$, Galactic latitude $|b|\lt $ 1.5°, and redshift $c z\lt 7500 \mathrm{kms}^{-1}$. We find that the extent of the Void is $\sim 58 \mathrm{Mpc}$ at these low Galactic latitudes. The galaxies in the Void tend to have lower HI masses (by approximately 0.25dex) compared to average density counterparts. We identified several likely small groups of galaxies, of which two groups (with 3 members and 5 members) in the Void show signs of filamentary substructure.

关键词： Surveys

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Coordinated cyber-attack detection model of cyber-physical power system based on the operating state data link

arXiv

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arXiv 2021年

作者： Wang, Lei Xu, Pengcheng Qu, Zhaoyang Bo, Xiaoyong Dong, Yunchang Zhang, Zhenming Li, Yang School of Electrical Engineering Northeast Electric Power University Jilin China Jilin Engineering Technology Research Center of Intelligent Electric Power Big Data Processing Jilin China Siping Power Supply Company of State Grid Jilin Electric Power Company Limited Siping China

Existing coordinated cyber-attack detection methods have low detection accuracy and efficiency and poor generalization ability due to difficulties dealing with unbalanced attack data samples, high data dimensionality, and noisy data sets. This paper proposes a model for cyber and physical data fusion using a data link for detecting attacks on a Cyber-Physical Power System (CPPS). Two-step principal component analysis (PCA) is used for classifying the system’s operating status. An adaptive synthetic sampling algorithm is used to reduce the imbalance in the categories’ samples. The loss function is improved according to the feature intensity difference of the attack event, and an integrated classifier is established using a classification algorithm based on the cost-sensitive gradient boosting decision tree (CS-GBDT). The simulation results show that the proposed method provides higher accuracy, recall, and F-Score than comparable algorithms. © 2021, CC BY-NC-ND.

关键词： Decision trees

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A Heterogeneous PIM Hardware-Software Co-Design for Energy-Efficient Graph Processing

A Heterogeneous PIM Hardware-Software Co-Design for Energy-E...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Yu Huang Long Zheng Pengcheng Yao Jieshan Zhao Xiaofei Liao Hai Jin Jingling Xue National Engineering Research Center for Big Data Technology and System/Service Computing Technology and System Lab/Cluster and Grid Computing Lab Huazhong University of Science and Technology China UNSW Sydney Australia

ISBN: (数字)9781728168760

ISBN: (纸本)9781728168777

Processing-In-Memory (PIM) is an emerging technology that addresses the memory bottleneck of graph processing. In general, analog memristor-based PIM promises high parallelism provided that the underlying matrix-structured crossbar can be fully utilized while digital CMOS-based PIM has a faster single-edge execution but its parallelism can be low. In this paper, we observe that there is no absolute winner between these two representative PIM technologies for graph applications, which often exhibit irregular workloads. To reap the best of both worlds, we introduce a new heterogeneous PIM hardware, called Hetraph, to facilitate energy-efficient graph processing. Hetraph incorporates memristor-based analog computation units (for high-parallelism computing) and CMOS-based digital computation cores (for efficient computing) on the same logic layer of a 3D die-stacked memory device. To maximize the hardware utilization, our software design offers a hardware heterogeneity-aware execution model and a workload offloading mechanism. For performance speedups, such a hardware-software co-design outperforms the state-of-the-art by 7.54 ×(CPU), 1.56 ×(GPU), 4.13× (memristor-based PIM) and 3.05× (CMOS-based PIM), on average. For energy savings, Hetraph reduces the energy consumption by 57.58× (CPU), 19.93× (GPU), 14.02 ×(memristor-based PIM) and 10.48 ×(CMOS-based PIM), on average.

关键词： Hardware Computer architecture Parallel processing Three-dimensional displays Computational modeling Graphics processing units Memristors

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Chirality-2 fermion induced Anti-Klein tunneling in 2D checkerboard lattice

arXiv

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arXiv 2024年

作者： Hua, Jiannan Wang, Z.F. Zhu, W. Chen, Weiwei Department of Physics School of Science Westlake University Zhejiang Hangzhou310024 China Institute of Natural Sciences Westlake Institute for Advanced Study Zhejiang Hangzhou310024 China Hefei National Research Center for Physical Sciences at the Microscale CAS Key Laboratory of Strongly-Coupled Quantum Matter Physics Department of Physics University of Science and Technology of China Anhui Hefei230026 China Hefei National Laboratory University of Science and Technology of China Anhui Hefei230088 China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province College of Science China Jiliang University Hangzhou310018 China

The quantum tunneling effect in the two-dimensional (2D) checkerboard lattice is investigated. By analyzing the pseudospin texture of the states in a 2D checkerboard lattice based on the low-energy effective Hamiltonian, we find that this system has a chiral symmetry with chirality equal to 2. Although compared to regular chiral fermions, its pseudospin orientation does not vary uniformly. This suggests that the perfect reflection chiral tunneling, also known as the anti-Klein tunneling, is expected to appear in checkerboard lattice as well. In order to verify the conjecture, we calculate the transmission probability and find that normally incident electron states can be perfectly reflected by the barrier with hole states inside, and vice versa. Furthermore, we also numerically calculate the tunneling conductance of the checkerboard nanotube using the recursive Green’s function method. The results show that a perfect on-off ratio can be achieved by confining the energy of the incident states within a certain range. It also suggests that, by tuning the barrier, the checkerboard nanotube is able to work as a perfect "band filter" or "tunneling field effect transistor", which transmits electrons selectively with respect to the pseudospin of the incident electrons. Copyright © 2024, The Authors. All rights reserved.

关键词： Nanotubes

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Shattered chain of trust: understanding security risks in cross-cloud IoT access delegation 20

Shattered chain of trust: understanding security risks in cr...

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Proceedings of the 29th USENIX Conference on Security Symposium

作者： Bin Yuan Yan Jia Luyi Xing Dongfang Zhao XiaoFeng Wang Deqing Zou Hai Jin Yuqing Zhang School of Cyber Science and Engineering Huazhong Univ. of Sci. & Tech. China and National Engineering Research Center for Big Data Technology and System Cluster and Grid Computing Lab Services Computing Technology and System Lab and Big Data Security Engineering Research Center and Indiana University Bloomington and Shenzhen Huazhong University of Science and Technology Research Institute China School of Cyber Engineering Xidian University China and National Computer Network Intrusion Protection Center University of Chinese Academy of Sciences China and Indiana University Bloomington Indiana University Bloomington School of Cyber Science and Engineering Huazhong Univ. of Sci. & Tech. China and National Engineering Research Center for Big Data Technology and System Cluster and Grid Computing Lab Services Computing Technology and System Lab and Big Data Security Engineering Research Center School of Computer Science and Technology Huazhong Univ. of Sci. & Tech. China and National Engineering Research Center for Big Data Technology and System Cluster and Grid Computing Lab Services Computing Technology and System Lab and Big Data Security Engineering Research Center Huazhong Univ. of Sci. & Tech. China National Computer Network Intrusion Protection Center University of Chinese Academy of Sciences China and School of Cyber Engineering Xidian University China

ISBN: (纸本)9781939133175

IoT clouds facilitate the communication between IoT devices and users, and authorize users' access to their devices. In this paradigm, an IoT device is usually managed under a particular IoT cloud designated by the device vendor, e.g., Philips bulbs are managed under Philips Hue cloud. Today's mainstream IoT clouds also support device access delegation across different vendors (e.g., Philips Hue, LIFX, etc.) and cloud providers (e.g., Google, IFTTT, etc.): for example, Philips Hue and SmartThings clouds support to delegate device access to another cloud such as Google Home, so a user can manage multiple devices from different vendors all through Google Home. Serving this purpose are the IoT delegation mechanisms developed and utilized by IoT clouds, which we found are heterogeneous and ad-hoc in the wild, in the absence of a standardized delegation protocol suited for IoT environments. In this paper, we report the first systematic study on real-world IoT access delegation, based upon a semi-automatic verification tool we developed. Our study brought to light the pervasiveness of security risks in these delegation mechanisms, allowing the adversary (e.g., Airbnb tenants, former employees) to gain unauthorized access to the victim's devices (e.g., smart locks) or impersonate the devices to trigger other devices. We confirmed the presence of critical security flaws in these mechanisms through end-to-end exploits on them, and further conducted a measurement study. Our research demonstrates the serious consequences of these exploits and the security implications of the practice today for building these mechanisms. We reported our findings to related parties, which acknowledged the problems. We further propose principles for developing more secure cross-cloud IoT delegation services, before a standardized solution can be widely deployed.

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Adaptive disentangled target representation for unsupervised domain adaptation in remote sensing segmentation

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Engineering Applications of Artificial Intelligence 2025年 156卷

作者： Lu, Runuo Dong, Shoubin Jia, Jianxin Wang, Xusheng Liu, Kai Chen, Jinsong Guo, Shanxin Zheng, Xiaorou Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis School of Computer Science and Engineering South China University of Technology Guangzhou510641 China Department of Photogrammetry and Remote Sensing Finnish Geospatial Research Institute EspooFI-02150 Finland Center for Geo-Spatial Information Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Engineering Laboratory of Ocean Environmental Big Data Analysis and Application Shenzhen518055 China

Due to the significant differences between the source and target domains, semantic segmentation models for remote sensing images trained on the source domain often struggle to generalize effectively to new target domains, leading to performance degradation. Most solutions disentangle features into domain-invariant features shared by both domains and domain-specific features unique to each domain, relying primarily on the domain-invariant features for model construction and inference. However, during this process, critical domain-specific features as essential information are often discarded as noise, leading to a reduction in segmentation accuracy. To address these issues, this study proposes an unsupervised domain adaptation, called ChameleonRS. ChameleonRS separates the domain-invariant features and the domain-specific features by disentanglement learning, and introduces a multi-level feature alignment module to enhance the representation of domain-invariant features. More importantly, it aligns predictions based on domain-invariant features with those based on fused invariant and specific features using contrastive learning, effectively capturing target-specific features. This study explores two cross-domain semantic segmentation tasks: (I) Geographic location variation. (II) Geographic location and imaging mode variation. Results show that under setting (I), ChameleonRS outperforms the state-of-the-art method by 4.79% in Intersection over Union (IoU) and 6.51% in the F1 score. Under setting (II), it achieves improvements of 4.46% and 4.82% in IoU and F1 score. Results demonstrate the superiority and adaptability of ChameleonRS under varying geographical and imaging conditions, effectively mitigating the generalization issues caused by distribution differences, and thereby promoting the development and application of remote sensing technologies in practical scenarios. © 2025 Elsevier Ltd

关键词： Semantic Segmentation

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Spara: An Energy-Efficient ReRAM-Based Accelerator for Sparse Graph Analytics Applications

Spara: An Energy-Efficient ReRAM-Based Accelerator for Spars...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Long Zheng Jieshan Zhao Yu Huang Qinggang Wang Zhen Zeng Jingling Xue Xiaofei Liao Hai Jin National Engineering Research Center for Big Data Technology and System/Service Computing Technology and System Lab/Cluster and Grid Computing Lab Huazhong University of Science and Technology China UNSW Sydney Australia

ISBN: (数字)9781728168760

ISBN: (纸本)9781728168777

Resistive random access memory (ReRAM) addresses the high memory bandwidth requirement challenge of graph analytics by integrating the computing logic in the memory. Due to the matrix-structured crossbar architecture, existing ReRAM-based accelerators, when handling real-world graphs that often have the skewed degree distribution, suffer from the severe sparsity problem arising from zero fillings and activation nondeterminism, incurring substantial ineffectual *** this paper, we observe that the sparsity sources lie in the consecutive mapping of source and destination vertex index onto the wordline and bitline of a crossbar. Although exhaustive graph reordering improves the sparsity-induced inefficiency, its totally-random (source and destination) vertex mapping leads to expensive overheads. This work exploits the insight in a mid-point vertex mapping with the random wordlines and consecutive bitlines. A cost-effective preprocessing is proposed to exploit the insight by rapidly exploring the crossbar-fit vertex reorderings but ignores the sparsity arising from activation dynamics. We present a novel ReRAM-based graph analytics accelerator, named Spara, which can maximize the workload density of crossbars dynamically by using a tightly-coupled bank parallel architecture further proposed. Results on real-world and synthesized graphs show that Spara outperforms GraphR and GraphSAR by 8.21 × and 5.01 × in terms of performance, and by 8.97 × and 5.68× in terms of energy savings (on average), while incurring a reasonable (

关键词： Indexes Electrodes Random access memory Parallel architectures Resistance Memory management

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Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges

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Science Bulletin 2019年第20期64卷 1540-1556页

作者： Kun Shi Yunlin Zhang Boqiang Qin Botian Zhou Taihu Laboratory for Lake Ecosystem Research State Key Laboratory of Lake Science and EnvironmentNanjing Institute of Geography and LimnologyChinese Academy ofSciencesNanjing210008China University of Chinese Academy of Sciences Beijing100049China Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of SciencesBeijing100101China Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing400714China

Timely monitoring, detection and quantification of cyanobacterial blooms are especially important for controlling public health risks and understanding aquatic ecosystem dynamics. Due to the advantages of simultaneous data acquisition over large geographical areas and high temporal coverage, remote sensing strongly facilitates cyanobacterial bloom monitoring in inland waters. We provide a comprehensive review regarding cyanobacterial bloom remote sensing in inland waters including cyanobacterial optical characteristics, operational remote sensing algorithms of chlorophyll, phycocyanin and cyanobacterial bloom areas, and satellite imaging applications. We conclude that there have many significant progresses in the remote sensing algorithm of cyanobacterial pigments over the past 30 years. The band ratio algorithms in the red and near-infrared(NIR) spectral regions have great potential for the remote estimation of chlorophyll a in eutrophic and hypereutrophic inland waters, and the floating algae index(FAI) is the most widely used spectral index for detecting dense cyanobacterial blooms. Landsat, MODIS(Moderate Resolution Imaging Spectroradiometer) and MERIS(MEdium Resolution Imaging Spectrometer) are the most widely used products for monitoring the spatial and temporal dynamics of cyanobacteria in inland waters due to the appropriate temporal, spatial and spectral resolutions. Future work should primarily focus on the development of universal algorithms, remote retrievals of cyanobacterial blooms in oligotrophic waters, and the algorithm applicability to mapping phycocyanin at a large spatial-temporal scale. The applications of satellite images will greatly improve our understanding of the driving mechanism of cyanobacterial blooms by combining numerical and ecosystem dynamics models.

关键词： Cyanobacterial blooms Inland waters Bio-optical properties Satellite MODIS

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