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Crank Call Detection Models Based on Call data of Telephone Subscribers

Journal of Physics: Conference Series 2020年第1期1673卷

作者： Wenbo Xie Zhen Liu Yan Fu Big Data Research Center University of Electronic Science and Technology of China Chengdu 611731 People's Republic of China Web Sciences Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 People's Republic of China

data explosion makes our life much more convenient than ever. For example, people always get timely news from Apps, and get interesting recommendations when shopping online. However, these conveniences come by probing people's private data, such as account information, search history, and chat records. Thus, if the management of data is not as secure as it supposes to be, many problems, e.g., crank calls, will arise and cause big troubles in people's lives. Although many security Apps have been developed to help mobile phone users stay away from crank calls, the users need to update Apps frequently due to their user-labels-based blacklist. These feedback-based systems depend on a large number of user actions that have significant lag. In this paper, we propose two crank call detection models to help operators mark crank callers based on the call data of telephone subscribers, in which the features are organized by different ways. One is a composited classification model, and the other is a convolutional neural network model based on the time-sliced data. The experiments show that the model applying convolutional neural network gets better accuracies in detecting crank calls.

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Lifelong Disk Failure Prediction via GAN-Based Anomaly Detection

Lifelong Disk Failure Prediction via GAN-Based Anomaly Detec...

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IEEE International Conference on Computer Design: VLSI in Computers and Processors, (ICCD)

作者： Tianming Jiang Jiangfeng Zeng Ke Zhou Ping Huang Tianming Yang Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China School of Computer Science & Technology Huazhong University of Science & Technology China School of Information Management Central China Normal University China Temple University USA Huanghuai University China

As a classical technique in storage systems, disk failure prediction aims at predicting impending disk failures in advance for high data reliability. Over the past decades, taking as input the SMART (Self-Monitoring, Analysis and Reporting technology) attributes, many supervised machine learning algorithms have been proven to be effective for disk failure prediction. However, these approaches heavily rely on the availability of substantial annotated failed disk data which unfortunately exhibits an extreme data imbalance, i.e., the number of failed disks is much smaller than that of healthy ones, resulting in suboptimal performance and even inability at the beginning of their deployment, i.e., cold starting problem. Inspired by the significant success achieved in GAN (Generative Adversarial Network) based anomaly detection, in this paper, we translate disk failure prediction into an anomaly detection problem. Specifically, we develop a novel Semi-supervised method for lifelong disk failure Prediction via Adversarial training, called SPA. The distinguishing feature of SPA from existing supervised approaches is that SPA is only trained on healthy disks, which avoids the traditional limitations of imbalance in datasets and eliminates the cold starting problem. Furthermore, a novel 2D image-like representation technique is proposed to enable the deployment of deep learning techniques and the automatic feature extraction. Experimental results on real-world SMART datasets demonstrate that, compared with the state-of-the-art supervised machine learning based methods, our approach predicts disk failures at a higher accuracy for the entire lifetime of models, i.e., both the initial period and the long-term usage.

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An Advanced Quantum-Resistant Signature Scheme for Cloud Based on Eisenstein Ring

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Computers, Materials & Continua 2018年第7期56卷 19-34页

作者： Faguo Wu Xiao Zhang Wang Yao Zhiming Zheng Lipeng Xiang Wanpeng Li Key Laboratory of Mathematics Informatics and Behavioral SemanticsMinistry of EducationSchool of Mathematics and Systems ScienceBeihang UniversityBeijing100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing100191China The Fifth Electronics Research Institute of Ministry of Industry and Information Technology Guangzhou510610China Department of Electrical and Electronic Engineering City University of LondonUK

Signature,widely used in cloud environment,describes the work as readily identifying its *** existing signature schemes in the literature mostly rely on the Hardness assumption which can be easily solved by quantum *** this paper,we proposed an advanced quantum-resistant signature scheme for Cloud based on Eisenstein Ring(ETRUS)which ensures our signature scheme proceed in a lattice with higher *** proved that ETRUS highly improve the performance of traditional lattice signature ***,the Norm of polynomials decreases significantly in ETRUS which can effectively reduce the amount of polynomials convolution ***,storage complexity of ETRUS is smaller than classical ***,according to all convolution of ETRUS enjoy lower degree polynomials,our scheme appropriately accelerate 56.37%speed without reducing its security level.

关键词： Signature quantum-resistant Eisenstein Ring ETRUS

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An Overview of General Theory of security

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China Communications 2017年第7期14卷 1-10页

作者： Min Lei Yixian Yang Xinxin Niu Yu Yang Jie Hao Information Security Center Beijing University of Posts and Telecommunications Guizhou University Guizhou Provincial Key Laboratory of Public Big Data Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology

Cyber security lacks comprehensive theoretical guidance. General security theory, as a set of basic security theory concepts, is intended to guide cyber security and all the other security work. The general theory of security aims to unify the main branches of cyber security and establish a unified basic theory. This paper proposal an overview on the general theory of security, which is devoted to constructing a comprehensive model of network security. The hierarchical structure of the meridian-collateral tree is described. Shannon information theory is employed to build a cyberspace security model. Some central concepts of security, i.e., the attack and defense, are discussed and several general theorems on security are presented.

关键词： cyber security network attack and defense meridian-collateral theory

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Errata to “On-Edge Multi-Task Transfer Learning: Model and Practice With data-Driven Task Allocation”

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IEEE Transactions on Parallel and Distributed Systems 2020年第11期31卷 2569-2569页

作者： Qiong Chen Zimu Zheng Chuang Hu Dan Wang Fangming Liu National Engineering Research Center for Big Data Technology and System Huazhong University of Science and Technology Wuhan China Edge Cloud Innovation Lab Technical Innovation Department Cloud BU Huawei Technologies Company Ltd. Shenzhen China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong

Presents corrections to author information for the above named paper.

关键词： Task analysis Resource management Technological innovation Computational modeling big data Service computing Computer science

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Interactive Ontology Matching Based on Evolutionary Algorithm

Interactive Ontology Matching Based on Evolutionary Algorith...

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International Conference on Computational Intelligence and security

作者： Xingsi Xue Junfeng Chen Aihong Ren College of Information Science and Engineering Intelligent Information Processing Research Center Fujian Key Lab for Automotive Electronics and Electric Drive Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of IOT Engineering Hohai University ChanZhou China School of Mathematics and Information Science Baoji University of Arts and Sciences Baoji China

ISBN: (数字)9781728160924

ISBN: (纸本)9781728160931

Since different ontologies are mostly developed independently, establishing meaningful links between their entities, so-called ontology matching, is critical to ensure their communication. Due to the complexity of the ontology matching problem, Evolutionary Algorithm (EA) can present a good methodology for determining ontology alignments. However, since none of the similarity measure can distinguish all the identical ontology entities in any context, ontology alignments generated by the automatic matching tools should be validated by the users to ensure their qualities. To improve the quality of the ontology alignment, in this work, a similarity measure is first proposed to calculate the similarity value of two ontology entities; then, an optimal model for ontology matching problem is constructed; after that, an EA-based automatic matcher is presented to solve the ontology matching problem, which can also adaptively determine the timing of getting user involved; and finally, the ontology concept hierarchy graph based reasoning approaches are proposed to tradeoff the user's workload and his work's effect. The experiment is conducted on the Interactive track provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with OAEI's participants show the effectiveness of our proposal.

关键词： Ontologies Graph theory Pattern matching Evolutionary computation

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Mapping essential urban land use categories in China(EULUC-China):preliminary results for 2018

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science Bulletin 2020年第3期65卷 182-187页

作者： Peng Gong Bin Chen Xuecao Li Han Liu Jie Wang Yuqi Bai Jingming Chen Xi Chen Lei Fang Shuailong Feng Yongjiu Feng Yali Gong Hao Gu Huabing Huang Xiaochun Huang Hongzan Jiao Yingdong Kang Guangbin Lei Ainong Li Xiaoting Li Xun Li Yuechen Li Zhilin Li Zhongde Li Chong Liu Chunxia Liu Maochou Liu Shuguang Liu Wanliu Mao Changhong Miao Hao Ni Qisheng Pan Shuhua Qi Zhehao Ren Zhuoran Shan Shaoqing Shen Minjun Shi Yimeng Song Mo Su Hoi Ping Suen Bo Sun Fangdi Sun Jian Sun Lin Sun Wenyao Sun Tian Tian Xiaohua Tong Yihsing Tseng Ying Tu Hong Wang Lan Wang Xi Wan Zongming Wang Tinghai Wu Yaowen Xie Jian Yang Jun Yang Man Yuan Wenze Yue Hongda Zeng Kuo Zhang Neng Zhang Tao Zhang Yu Zhang Feng Zhao Yichen Zheng Qiming Zhou Nicholas Clinton Zhiliang Zhu Bing Xu Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Tsinghua Urban Institute Tsinghua UniversityBeijing 100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing 100084China Department of Land Air and Water ResourcesUniversity of CaliforniaDavisCA 95616-8627USA Department of Geological and Atmospheric Sciences Iowa State UniversityAmesIA 50011USA State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China AI for Earth Laboratory Cross-Strait InstituteTsinghua UniversityBeijing 100084China International Institute for Earth System Sciences Nanjing UniversityNanjing 210093China Research Center for Ecology and Environment of Central Asia Chinese Academy of SciencesUrumchi 830011China Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China National Engineering Laboratory for Applied Technology in Forestry&Ecology in South China College of Life Science and TechnologyCentral South University of Forestry and TechnologyChangsha 410004China College of Surveying&Geo-Informatics Tongji UniversityShanghai 200092China Department of Urban Planning College of Architecture and Urban PlanningTongji UniversityShanghai 200092China Beijing Institute of Urban Planning Beijing 100045China Department of Urban Planning School of Urban DesignWuhan UniversityWuhan 430072China College of Earth Sciences Jilin UniversityChangchun 130061China Research Center for Digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Institute of Remote Sensing and Geographic Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Department of Urban and Regional Planning School of Geography and PlanningSun Yat-sen Univ

Land use reflects human activities on *** land use is the highest level human alteration on Earth,and it is rapidly changing due to population increase and *** areas have widespread effects on local hydrology,climate,biodiversity,and food production[1,2].However,maps,that contain knowledge on the distribution,pattern and composition of various land use types in urban areas,are limited to city *** mapping standard on data sources,methods,land use classification schemes varies from city to city,due to differences in financial input and skills of mapping *** address various national and global environmental challenges caused by urbanization,it is important to have urban land uses at the national and global scales that are derived from the same or consistent data sources with the same or compatible classification systems and mapping *** is because,only with urban land use maps produced with similar criteria,consistent environmental policies can be made,and action efforts can be compared and assessed for large scale environmental ***,despite of the fact that a number of urban-extent maps exist at global scales[3,4],more detailed urban land use maps do not exist at the same *** at big country or regional levels such as for the United States,China and European Union,consistent land use mapping efforts are rare[5,6](e.g.,https://***/open_land_use/).

关键词： EULUC-China 土地利用类型

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Towards the Trust-Enhancements of Single Sign-On Services

Towards the Trust-Enhancements of Single Sign-On Services

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IEEE Conference on Dependable and Secure Computing

作者： Xuhua Bao Xiaokun Zhang Jingqiang Lin Dawei Chu Qiongxiao Wang Fengjun Li Legendsec Information Technology (Beijing) Inc. CHINA Joint Laboratory of Institute of Information Engineering Chinese Academy of Sciences and QiAnXin Group Academy of Opto-Electronics Chinese Academy of Sciences State Key Laboratory of Information Security Chinese Academy of Sciences Data Assurance and Communication Security Research Center Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences Department of Electrical Engineering and Computer Science University of Kansas USA

Single sign-on (SSO) becomes popular as the identity management and authentication infrastructure in the Internet. A user receives an SSO ticket after being authenticated by the identity provider (IdP), and this IdP-issued ticket enables him to sign onto the relying party (RP). However, there are vulnerabilities (e.g., Golden SAML) that allow attackers to arbitrarily issue SSO tickets and then sign onto any RP on behalf of any user. Meanwhile, several incidents of certification authorities (CAs) also indicate that the trusted third party of security services is not so trustworthy as expected, and fraudulent TLS server certificates are signed by compromised or deceived CAs to launch TLS man-in-the-middle attacks. Various approaches are then proposed to tame the absolute authority of (compromised) CAs, to detect or prevent fraudulent TLS server certificates in the TLS handshakes. The trust model of SSO services is similar to that of certificate services. So this paper investigates the defense strategies of these trust-enhancements of certificate services, and attempts to apply these strategies to SSO to derive the trust-enhancements applicable in the SSO services. Our analysis derives (a) some security designs which have been commonly-used in the SSO services or non-SSO authentication services, and (b) two schemes effectively improving the trustworthiness of SSO services, which are not widely discussed or adopted.

关键词： Servers Public key Browsers Authentication Authorization Pins

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Future Changes in Rainy Seasons in the Upper Blue Nile Basin: Impacts on Agriculture and Water Resources

Natural Hazards Research

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Natural Hazards research 2025年

作者： Fekadie Bazie Enyew Dejene Sahlu Gashaw Bimrew Tarekegn Yakob Umer Belen Marti-Cardona Bedassa R. Cheneka Daniel Asfaw Bekele Daniel Ayalew Mengistu Sarkawt Hama Zinaw D. Shenga Sisay E. Debele Institute of Disaster Risk Management and Food Security Studies Bahir Dar University P.O. Box 5501 Bahir Dar Ethiopia International Water Management Institute Hatfield Gardens 333 Grosvenor Street Hatfield Pretoria South Africa School of Sustainability Civil and Environmental Engineering Faculty of Engineering and Physical Sciences University of Surrey Guildford GU2 7XH United Kingdom Biology Department Utrecht University The Netherlands University of Antwerp Belgium Department of Geography and Environmental Studies Bahir Dar University P.O. Box 79 Bahir Dar Ethiopia Geospatial Data and Technology Center (GDTC) Bahir Dar University P.O. Box 79 Bahir Dar Ethiopia Global Centre for Clean Air Research Department of Civil and Environmental Engineering Faculty of Engineering and Physical Sciences University of Surrey Guildford GU2 7XH United Kingdom Department of Chemistry College of Science University of Sulaimani Sulaimani City 46001 Kurdistan Region Iraq Slovak Hydrometeorological Institute Jeséniova 17 833 15 Bratislava Slovak Republic Department of Global Health and Development Faculty of Public Health and Policy London School of Hygiene & Tropical Medicine London WC1H 9SH UK

Changing climate is increasingly influencing the rainy seasons and posing significant challenges for agriculture and water resource management in vulnerable regions. The study examines the spatiotemporal variation of rainy seasons in the Upper Blue Nile Basin (UBNB) of Northwestern Ethiopia using projections from the CMIP6 climate models to assess potential impacts on agricultural and water planning. We analyzed observed and projected precipitation data across three Shared Socioeconomic Pathway (SSP) scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5, spanning near-term (2015-2044), mid-term (2045-2074), and long-term (2075-2100) periods. To correct systematic biases in model outputs, a power transformation technique was applied to precipitation data from seven CMIP6 models. The finding of the study showed that the INM-CM5-0 model is the most accurate in simulating precipitation patterns, forming the basis for our detailed analysis. Our findings reveal significant shifts in the timing and duration of rainy seasons across all scenarios, with more pronounced changes under the highest emission pathways, SSP5-8.5. The SSP5-8.5 scenario indicates the most substantial extension in the length of rainy season, particularly in lowland areas, due to both earlier onset and delayed cessation. Conversely, highland and midland regions are projected to experience shorter rainy seasons, lasting between 82 and 130 days, driven by delayed onset and earlier cessation. These shifts could profoundly affect agricultural productivity, necessitating adjustments in planting and harvesting schedules by several months. Under high-emission scenarios, crop cycles may become misaligned with traditional planting windows, especially in highland areas where shorter rainy seasons may constrain crop viability. This study highlights the urgent need for adaptive strategies, such as the practice of early-maturing crop varieties, to enhance resilience to the change of projected seasonal rainfall patterns. Proac

关键词： Rainy Season Patterns Climate Change Impact CMIP6 Models Bias Correction Upper Blue Nile Basin

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Erratum to “High-Efficiency Min-Entropy Estimation Based on Neural Network for Random Number Generators”

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security and Communication Networks 2020年第1期2020卷

作者： Na Lv Tianyu Chen Shuangyi Zhu Jing Yang Yuan Ma Jiwu Jing Jingqiang Lin State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 *** Data Assurance and Communications Security Research Center Chinese Academy of Sciences Beijing 100093 *** School of Cyber Security University of Chinese Academy of Sciences Beijing 100093 *** China Information Technology Security Evaluation Center Beijing 100085 *** School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100093 ***

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