检索结果-内蒙古大学图书馆

Erratum to “Quantifying the need for supervised machine learning in conducting live forensics analysis of emergent configurations (ECO) in IoT environments” [Forensic Sci. Int.: Rep. 2 (2020) 100122]

引用

Forensic science International: Reports 2020年 2卷 100135-100135页

作者： Kebande, Victor R. Ikuesan, Richard A. Karie, Nickson M. Alawadi, Sadi Choo, Kim-Kwang Raymond Al-Dhaqm, Arafat Department of Computer Science Malmö University Sweden Cyber and Network Security Department Science and Technology Division Community College of Qatar Qatar School of Science Edith Cowan University Australia Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio TX 78249-0631 USA School of Computing Faculty of Engineering Universiti Teknologi Malysia Johor Malaysia

来源：评论

学校读者我要写书评

暂无评论

Relation Structure-Aware Heterogeneous Graph Neural Network

Relation Structure-Aware Heterogeneous Graph Neural Network

引用

IEEE International Conference on Data Mining (ICDM)

作者： Shichao Zhu Chuan Zhou Shirui Pan Xingquan Zhu Bin Wang Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Faculty of Information Technology Monash University Melbourne Australia Dept. of Computer & Electrical Engineering and Computer Science Florida Atlantic University Boca Raton USA Xiaomi AI Lab Beijing China

Heterogeneous graphs with different types of nodes and edges are ubiquitous and have immense value in many applications. Existing works on modeling heterogeneous graphs usually follow the idea of splitting a heterogeneous graph into multiple homogeneous subgraphs. This is ineffective in exploiting hidden rich semantic associations between different types of edges for large-scale multi-relational graphs. In this paper, we propose Relation Structure-Aware Heterogeneous Graph Neural Network (RSHN), a unified model that integrates graph and its coarsened line graph to embed both nodes and edges in heterogeneous graphs without requiring any prior knowledge such as metapath. To tackle the heterogeneity of edge connections, RSHN first creates a Coarsened Line Graph Neural Network (CL-GNN) to excavate edge-centric relation structural features that respect the latent associations of different types of edges based on coarsened line graph. After that, a Heterogeneous Graph Neural Network (H-GNN) is used to leverage implicit messages from neighbor nodes and edges propagating among nodes in heterogeneous graphs. As a result, different types of nodes and edges can enhance their embedding through mutual integration and promotion. Experiments and comparisons, based on semi-supervised classification tasks on large scale heterogeneous networks with over a hundred types of edges, show that RSHN significantly outperforms state-of-the-arts.

关键词：

来源：评论

学校读者我要写书评

暂无评论

E-trade Management System Architecture

E-trade Management System Architecture

引用

IEEE International Conference on Advanced Trends in Information Theory (ATIT)

作者： Oleg Pursky Anna Selivanova Oleksander Kharchenko Pavlo Demidov Volodymyr Kulazhenko department of computer science Kyiv national university of trade and economics Kyiv Ukraine department of software engineering and cyber security Kyiv national university of trade and economics Kyiv Ukraine department of cybernetics and system analysis Kyiv national university of trade and economics Kyiv Ukraine

ISBN: (数字)9781728161440

ISBN: (纸本)9781728161457

In this work we present the model for construction of e-trade management system architecture which consists of two basic blocks: the landing Web-pages management unit of the online store is responsible for interacting with the user, receiving orders and collecting primary information and Web-enterprise management unit, responsible for processing orders, their delivery, and all enterprise's business processes realization. We have focused our attention to developing an architecture model for e-trady management system. A service-oriented architecture (SOA) using enterprise service bus (ESB) concept is offered for architectural implementation. In developed e-trade management system architecture we used the method of integrating complex information systems within the information environment based on SOA and ESB technologies, which represents an independent, integrative subsystem for relatively integrated information systems. Typical information systems that belong to the e-trade system are used as services. These web-based services should be developed and used to enhance ESB efficiency. Such web-services implement SOAP and use WSDL (Web Services Description Language), as well as UDDI specification (Universal Description, Discovery and Integration). At that, each typical information system is simultaneously data supplier and data consumer. Each information system handles its own data class, while being able to both transmit and receive, adjust and modify data according to operational information from other information systems within main business processes.

关键词： Service-oriented architecture Information systems Web services

来源：评论

学校读者我要写书评

暂无评论

Coherence-based automated essay scoring using self-attention 17th

Coherence-based automated essay scoring using self-attention

引用

17th China National Conference on Computational Linguistics, CCL 2018 and 6th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2018

作者： Li, Xia Chen, Minping Nie, Jianyun Liu, Zhenxing Feng, Ziheng Cai, Yingdan Key Laboratory of Language Engineering and Computing Guangdong University of Foreign Studies Guangzhou China School of Information Science and Technology/School of Cyber Security Guangdong University of Foreign Studies Guangzhou China Department of Computer Science and Operations Research University of Montreal Montreal Canada

ISBN: (纸本)9783030017156

Automated essay scoring aims to score an essay automatically without any human assistance. Traditional methods heavily rely on manual feature engineering, making it expensive to extract the features. Some recent studies used neural-network-based scoring models to avoid feature engineering. Most of them used CNN or RNN to learn the representation of the essay. Although these models can cope with relationships between words within a short distance, they are limited in capturing long-distance relationships across sentences. In particular, it is difficult to assess the coherence of the essay, which is an essential criterion in essay scoring. In this paper, we use self-attention to capture useful long-distance relationships between words so as to estimate a coherence score. We tested our model on two datasets (ASAP and a new non-native speaker dataset). In both cases, our model outperforms the existing state-of-the-art models. © Springer Nature Switzerland AG 2018.

关键词： Automation

来源：评论

学校读者我要写书评

暂无评论

Structural transition in interdependent networks with regular interconnections

引用

Physical Review E 2019年第1期99卷 012311-012311页

作者： Xiangrong Wang Robert E. Kooij Yamir Moreno Piet Van Mieghem Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands iTrust Centre for Research in Cyber Security Singapore University of Technology and Design Singapore Institute for Biocomputation and Physics of Complex Systems (BIFI) University of Zaragoza Zaragoza 50009 Spain Department of Theoretical Physics University of Zaragoza Zaragoza 50009 Spain ISI Foundation Turin Italy

Networks are often made up of several layers that exhibit diverse degrees of interdependencies. An interdependent network consists of a set of graphs G that are interconnected through a weighted interconnection matrix B, where the weight of each intergraph link is a non-negative real number p. Various dynamical processes, such as synchronization, cascading failures in power grids, and diffusion processes, are described by the Laplacian matrix Q characterizing the whole system. For the case in which the multilayer graph is a multiplex, where the number of nodes in each layer is the same and the interconnection matrix B=pI, I being the identity matrix, it has been shown that there exists a structural transition at some critical coupling p*. This transition is such that dynamical processes are separated into two regimes: if p>p*, the network acts as a whole; whereas when p

关键词： Collective behavior in networks Dynamics of networks Network phase transitions Topological phase transition

来源：评论

学校读者我要写书评

暂无评论

NTIRE 2021 challenge on video super-resolution

arXiv

引用

arXiv 2021年

作者： Son, Sanghyun Lee, Suyoung Nah, Seungjun Timofte, Radu Lee, Kyoung Mu Chan, Kelvin C.K. Zhou, Shangchen Xu, Xiangyu Loy, Chen Change Jiang, Boyuan Lin, Chuming Dong, Yuchun Luo, Donghao Chu, Wenqing Ji, Xiaozhong Yang, Siqian Tai, Ying Wang, Chengjie Li, Jilin Huang, Feiyue Chen, Chengpeng Chu, Xiaojie Zhang, Jie Lu, Xin Chen, Liangyu Lin, Jing Du, Guodong Hao, Jia Zou, Xueyi Zhang, Qi Jiang, Lielin Li, Xin Zheng, He Liu, Fanglong He, Dongliang Li, Fu Dang, Qingqing Yi, Peng Wang, Zhongyuan Jiang, Kui Jiang, Junjun Ma, Jiayi Chen, Yuxiang Wang, Yutong Liu, Ting Sun, Qichao Liang, Huanwei Li, Yiming Li, Zekun Ruan, Zhubo Shang, Fanjie Guo, Chen Li, Haining Luo, Renjun Shen, Longjie Zafirouli, Kassiani Karageorgos, Konstantinos Konstantoudakis, Konstantinos Dimou, Anastasios Daras, Petros Song, Xiaowei Zhuo, Xu Liu, Hanxi Guo, Mengxi Li, Junlin Li, Yu Zhu, Ye Wang, Qing Zhao, Shijie Sun, Xiaopeng Zhan, Gen Xie, Tangxin Jia, Yu Lu, Yunhua Zhang, Wenhao Sun, Mengdi Michelini, Pablo Navarrete Zhang, Xueheng Jiang, Hao Chen, Zhiyu Chen, Li Xiong, Zhiwei Xiao, Zeyu Xu, Ruikang Cheng, Zhen Fu, Xueyang Song, Fenglong Luo, Zhipeng Yao, Yuehan Dutta, Saikat Shah, Nisarg A. Das, Sourya Dipta Zhao, Peng Shi, Yukai Liu, Hongying Shang, Fanhua Liu, Yuanyuan Chen, Fei Yu, Fangxu Gao, Ruisheng Bai, Yixin Heo, Jeonghwan Yue, Shijie Li, Chenghua Li, Jinjing Zheng, Qian Gang, Ruipeng Song, Ruixia Wee, Seungwoo Jeong, Jechang Li, Chen Wen, Geyingjie Chai, Xinning Song, Li Department of ECE ASRI SNU Korea Republic of Computer Vision Lab ETH Zurich Switzerland S-Lab Nanyang Technological University Singapore YouTu Lab Tencent East China Normal University China Megvii Peking University China Fudan University China Noah's Ark Lab Huawei Canada Technologies Co. Ltd Baidu Inc National Engineering Research Center for Multimedia Software Wuhan University China School of Computer Science and Technology Harbin Institute of Technology China Electronic Information School Wuhan University China School of Computer Science and Engineering University of Electronic Science and Technology of China China MTlab Meitu Inc Xidian university China ITI CERTH Greece Southeast University China Tencent PCG South China University of Technology China ByteDance Sun Yat-Sen University China Electronic Technology Cyber Security Co. Ltd. AIoT R&D Centre BOE Technology Group Co. Ltd. Shanghai Jiao Tong University China University of Science and Technology of China China Huawei Noah's Ark Lab DeepBlue Technology Shanghai Co. Ltd Indian Institute of Technology Madras India Indian Institute of Technology Jodhpur India Jadavpur University India Xidian University China Hanyang University Korea Republic of NCUT China CASIA China CUC China NRTA China

Super-Resolution (SR) is a fundamental computer vision task that aims to obtain a high-resolution clean image from the given low-resolution counterpart. This paper reviews the NTIRE 2021 Challenge on Video Super-Resolution. We present evaluation results from two competition tracks as well as the proposed solutions. Track 1 aims to develop conventional video SR methods focusing on the restoration quality. Track 2 assumes a more challenging environment with lower frame rates, casting spatio-temporal SR problem. In each competition, 247 and 223 participants have registered, respectively. During the final testing phase, 14 teams competed in each track to achieve state-of-the-art performance on video SR tasks. © 2021, CC BY-NC-ND.

关键词： Optical resolving power

来源：评论

学校读者我要写书评

暂无评论

Targeted Malicious Email Detection using Hypervisor-based Dynamic Analysis and Ensemble Learning

Targeted Malicious Email Detection using Hypervisor-based Dy...

引用

IEEE Global Communications Conference

作者： Jian Zhang Zhaojun Gu Wenzhen Li Liangyi Gong Jeffrey Wu School of Computer Science and Engineering Tianjin University of Technology College of Cyber Science Nankai University Tianjin China School of Computer Science and Engineering Tianjin University of Technology Tianjin China School of Software and BNRist Tsinghua University Beijing China Information Security Evaluation Center of Civil Aviation Civil Aviation University of China Tianjin China Jiaxing Chenxiang Information Technology Co. Ltd. Jiaxing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

At present, email is still one of the most frequently used communication tools for organizations and individuals. With the leakage of personal privacy information, targeted malicious email (TME) is becoming a prominent targeted cyber attack vector in today's Internet. This type of attack often uses personal information, about an individual, group of individuals, or an organization, to make a TME more believable and personalized. TME is effective to penetrate email defense system because it is fundamentally difficult for traditional email security method to distinguish legitimate emails from malicious emails. And TMEs often contain malicious URLs or malicious attachments, which are extremely aggressive and destructive. In order to effectively deal with this new type of malicious email attack, this paper proposes a dynamic detection method for malicious email. We simulate the recipient opening the email in the virtual machine (VM), accessing the URL and activating the attachment. And we use the virtual machine introspection (VMI) and memory forensics analysis (MFA) technology to obtain the dynamic features of the email by the out-of-VM. Then we use AdaBoostM1 ensemble learning method and Voting combination strategy to combine three base classifiers such as BayesNet, SMO and J48 to build a powerful classification model for detecting TME attacks. The AdaBoostM1 classifier achieved the high detection rates, with an AUC of 0.997, true positive rate (TPR) of 0.997, and false positive rate (FPR) of 0.015. In addition, our proposed detection method is superior to the 56 anti-virus engines on VirusTotal and most of the existing research works.

关键词： Electronic mail Feature extraction Virtual machining Unsolicited e-mail Uniform resource locators Learning systems

来源：评论

学校读者我要写书评

暂无评论

Towards the Trust-Enhancements of Single Sign-On Services

Towards the Trust-Enhancements of Single Sign-On Services

引用

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

来源：评论

学校读者我要写书评

暂无评论

A blockchain-based architecture framework for secure sharing of personal health data 20

A blockchain-based architecture framework for secure sharing...

引用

20th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2018

作者： Amofa, Sandro Sifah, Emmanuel Boateng Obour Agyekum, Kwame O.-B. Abla, Smahi Xia, Qi Gee, James C. Gao, Jianbin School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Center for Cyber Security University of Electronic Science and Technology of China Chengdu China Department of Radiology University of Pennsylvania Philadelphia United States School of Resource and Enviroment Center for Digital Health University of Electronic Science and Technology China

ISBN: (纸本)9781538642948

Health information exchanges have been popular for some time with their advantages known and widely researched. In spite of their utility in increasing provider efficiency and decreasing administrative costs, one challenge that has persisted is the data owners inability to control data after transmission. The lack of technical mechanisms to effectively control patients' health data in the network significantly affects participation of health and medical institutions while perpetrating the silo-based data management that locks value and potential inherent in the data. This not only affects researchers due to the lack of data for research and analysis but the quality of life of *** present a blockchain-supported architectural framework for secure control of personal data in a health information exchange by pairing user-generated acceptable use policies with smart contracts. We highlight the merits of our system, its user-centric focus and also show experimental results along with directions for extending our work. The framework introduces minimal risk to data by architecting a mechanism for controlling data after sharing. In adopting our framework, health service providers can deliver a stronger assurance for data management than is possible with current systems. © 2018 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Domain-Adversarial Graph Neural Networks for Text Classification

Domain-Adversarial Graph Neural Networks for Text Classifica...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Man Wu Shirui Pan Xingquan Zhu Chuan Zhou Lei Pan Dept. of Computer & Electrical Engineering and Computer Science Florida Atlantic University Boca Raton USA Faculty of Information Technology Monash University Melbourne Australia Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China School of Information Technology Deakin University Geelong VIC Australia

Text classification, in cross-domain setting, is a challenging task. On the one hand, data from other domains are often useful to improve the learning on the target domain; on the other hand, domain variance and hierarchical structure of documents from words, key phrases, sentences, paragraphs, etc. make it difficult to align domains for effective learning. To date, existing cross-domain text classification methods mainly strive to minimize feature distribution differences between domains, and they typically suffer from three major limitations - (1) difficult to capture semantics in non-consecutive phrases and long-distance word dependency because of treating texts as word sequences, (2) neglect of hierarchical coarse-grained structures of document for feature learning, and (3) narrow focus of the domains at instance levels, without using domains as supervisions to improve text classification. This paper proposes an end-to-end, domain-adversarial graph neural networks (DAGNN), for cross-domain text classification. Our motivation is to model documents as graphs and use a domain-adversarial training principle to lean features from each graph (as well as learning the separation of domains) for effective text classification. At the instance level, DAGNN uses a graph to model each document, so that it can capture non-consecutive and long-distance semantics. At the feature level, DAGNN uses graphs from different domains to jointly train hierarchical graph neural networks in order to learn good features. At the learning level, DAGNN proposes a domain-adversarial principle such that the learned features not only optimally classify documents but also separates domains. Experiments on benchmark datasets demonstrate the effectiveness of our method in cross-domain classification tasks.

关键词：

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：