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arXiv 2021年

作者： Ma, Ke Xu, Qianqian Zeng, Jinshan Cao, Xiaochun Huang, Qingming The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China The Artificial Intelligence Research Center Peng Cheng Laboratory Shenzhen518055 China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China The School of Computer and Information Engineering Jiangxi Normal University Jiangxi Nanchang330022 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China The School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China The Key Laboratory of Big Data Mining and Knowledge Management The School of Economics and Management University of Chinese Academy of Sciences Beijing100049 China

As pairwise ranking becomes broadly employed for elections, sports competitions, recommendation, information retrieval and so on, attackers have strong motivation and incentives to manipulate or disrupt the ranking list. They could inject malicious comparisons into the training data to fool the target ranking algorithm. Such a technique is called "poisoning attack" in regression and classification tasks. In this paper, to the best of our knowledge, we initiate the first systematic investigation of data poisoning attack on the pairwise ranking algorithms, which can be generally formalized as the dynamic and static games between the ranker and the attacker, and can be modeled as certain kinds of integer programming problems mathematically. To break the computational hurdle of the underlying integer programming problems, we reformulate them into the distributionally robust optimization (DRO) problems, which are computational tractable. Based on such DRO formulations, we propose two efficient poisoning attack algorithms and establish the associated theoretical guarantees including the existence of Nash equilibrium and the generalization ability bounds. The effectiveness of the suggested poisoning attack strategies is demonstrated by a series of toy simulations and several real data experiments. These experimental results show that the proposed methods can significantly reduce the performance of the ranker in the sense that the correlation between the true ranking list and the aggregated results with toxic data can be decreased dramatically. © 2021, CC BY-NC-ND.

关键词： Toys

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Superposed Transparency Effect and Entanglement Generation with Hybrid System of Photonic Molecule and Dipole Emitter

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Chinese Physics Letters 2019年第3期36卷 41-44页

作者： Ji-Bing Yuan Zhao-Hui Peng Shi-Qing Tang Deng-Yu Zhang College of Physics and Electronic Engineering and Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal University Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics and Synergetic Innovation Center for Quantum Effects and ApplicationsHunan Normal University Institute of Modern Physics and Department of Physics Hunan University of Science and Technology

We theoretically investigate the transparency effect with a hybrid system composed of a photonic molecule and dipole emitter. It is shown that the transparency effect incorporates both the coupled resonator-induced transparency(CRIT) effect and the dipole-induced transparency(DIT) effect. It is found that the superposed transparency windows are consistently narrower than the CRIT and DIT transparency windows. Benefiting from the superposed transparency effect, the photonic Faraday rotation effect could be realized in the photonic molecule system, which is useful for entanglement generation and quantum information processing.

关键词： DIT Transparency Photonic Molecule Emitter

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Attack intent analysis method based on attack path graph 9

Attack intent analysis method based on attack path graph

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9th International Conference on Communication and Network Security, ICCNS 2019

作者： Chen, Biqiong Liu, Yanhua Li, Shijin Gao, Xiaoling College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou Fujian China

ISBN: (纸本)9781450376624

With the rapid development of network technology, network security problems are gradually increasing, and the network attack situation is very severe. In a complex attack scenario, timely detection of potential attack behaviors and timely identification and pre-judgment of attack intentions are important components of security risks. However, the attack behavior in the network presents complexity, multi-step and uncertainty, which brings new technical challenges to attack intent analysis. Aiming at the problem that the attack intention of multi-step complex attack is difficult to identify, this paper proposes an attack intention analysis method based on attack path graph. Firstly, aiming at the multi-step complex attack behavior analysis problem, the key asset assessment technology is used to find out the key assets in the network system, and the hypothetical attack intention is generated according to the security protection requirements of the network system. Then, it is difficult to manually construct the attack path map in the large-scale network, and the automatic generation of the attack path map is realized. Finally, a method of network attack intent identification is proposed and a calculation method of attack intent probability is designed, which improves the efficiency and accuracy of attack intent recognition. © 2019 Association for Computing Machinery.

关键词： Uncertainty analysis

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A comprehensive assessment method of asset importance for key asset protection 9

A comprehensive assessment method of asset importance for ke...

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9th International Conference on Communication and Network Security, ICCNS 2019

作者： Gao, Xiaoling Liu, Yanhua Qiu, Yanbin Liu, Huajun College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou Fujian China

ISBN: (纸本)9781450376624

In a given system network, an important prerequisite for security risk control is how to accurately calculate the impact of different host assets in the topology on the spread of attack risk. In this regard, we propose a comprehensive asset importance assessment model for critical asset protection. First, the importance of local static assets in the topology was evaluated using three methods: degree centrality, mediation centrality, and closeness centrality. At the same time, PageRank was used to assess the importance of local dynamic assets for asset level changes. By combining the above two methods, and using K-CORE to evaluate the core position of the host in the network topology as the global weight indicator of the importance of assets. The comprehensive evaluation results of the importance of topology-oriented assets was finally obtained, and the validity of the model was verified through the experiment of the simulation ER random network. © 2019 Association for Computing Machinery.

关键词： Network topology

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Enhanced Sparse Model for Blind Deblurring 16th

Enhanced Sparse Model for Blind Deblurring

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16th European Conference on computer Vision, ECCV 2020

作者： Chen, Liang Fang, Faming Lei, Shen Li, Fang Zhang, Guixu Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology East China Normal University Shanghai China School of Software Engineering East China Normal University Shanghai China School of Mathematical Sciences East China Normal University Shanghai China

ISBN: (纸本)9783030585945

Existing arts have shown promising efforts to deal with the blind deblurring task. However, most of the recent works assume the additive noise involved in the blurring process to be simple-distributed (i.e. Gaussian or Laplacian), while the real-world case is proved to be much more complicated. In this paper, we develop a new term to better fit the complex natural noise. Specifically, we use a combination of a dense function (i.e. l2) and a newly designed enhanced sparse model termed as le, which is developed from two sparse models (i.e. l1 and l0), to fulfill the task. Moreover, we further suggest using le to regularize image gradients. Compared to the widely-adopted l0 sparse term, le can penalize more insignificant image details (Fig. 1). Based on the half-quadratic splitting method, we provide an effective scheme to optimize the overall formulation. Comprehensive evaluations on public datasets and real-world images demonstrate the superiority of the proposed method against state-of-the-art methods in terms of both speed and accuracy. © 2020, Springer Nature Switzerland AG.

关键词： Additive noise

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A Comprehensive Assessment Method of Asset Importance for key Asset Protection 2019

A Comprehensive Assessment Method of Asset Importance for Ke...

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Proceedings of the 2019 the 9th International Conference on Communication and Network Security

作者： Xiaoling Gao Yanhua Liu Yanbin Qiu Huajun Liu College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou Fujian China

ISBN: (纸本)9781450376624

关键词： Centrality PageRank Asset importance key asset protection K-CORE

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The aging effect in evolving scientific citation networks

arXiv

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arXiv 2021年

作者： Hu, Feng Ma, Lin Zhan, Xiu-Xiu Zhou, Yinzuo Liu, Chuang Zhao, Haixing Zhang, Zi-Ke School of Computer Qinghai Normal University Xining810016 China Key Laboratory of Tibetan Information Processing Ministry of Education Xining810008 China Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province Xining810008 China Alibaba Research Center for Complexity Sciences Hangzhou Normal University Hangzhou311121 China Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands College of Media and International Culture Zhejiang University Hangzhou310058 China

The study of citation networks is of interest to the scientific community. However, the underlying mechanism driving individual citation behavior remains imperfectly understood, despite the recent proliferation of quantitative research methods. Traditional network models normally use graph theory to consider articles as nodes and citations as pairwise relationships between them. In this paper, we propose an alternative evolutionary model based on hypergraph theory in which one hyperedge can have an arbitrary number of nodes, combined with an aging effect to reflect the temporal dynamics of scientific citation behavior. Both theoretical approximate solution and simulation analysis of the model are developed and validated using two benchmark datasets from different disciplines, i.e. publications of the American Physical Society (APS) and the Digital Bibliography & Library Project (DBLP). Further analysis indicates that the attraction of early publications will decay exponentially. Moreover, the experimental results show that the aging effect indeed has a significant influence on the description of collective citation patterns. Shedding light on the complex dynamics driving these mechanisms facilitates the understanding of the laws governing scientific evolution and the quantitative evaluation of scientific outputs. © 2021, CC BY.

关键词： Graph theory

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A data clustering strategy for enhancing mutual privacy in healthcare system of IoT

A data clustering strategy for enhancing mutual privacy in h...

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2019 IEEE International Conferences on Ubiquitous Computing and Communications and Data Science and Computational Intelligence and Smart Computing, Networking and Services, IUCC/DSCI/SmartCNS 2019

作者： Guo, Xuancheng Lin, Hui Xu, Chuanfeng Lin, Wenzhong School of Mathematics and Computer Science Fujian Normal University Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9781728152097

Recent advances in the healthcare system of Internet of Things (IoT) has led to a generation of a large amount of physic sensor data. Data analyst collects and analyzes these sensor data through wireless sensor network, so as to provide some treatment advices to physicians and patients. As a common data mining method, the k-means clustering algorithm is being applied to process large-scale sensor data. However, it also poses a threat of privacy leakage in the specific application process. To enhance the privacy in healthcare system of IoT, mutual privacypreserving k-means strategy (M-PPKS) based on homomorphic encryption is proposed in this paper, which neither discloses an individual's private information nor leaks the cluster center's characteristic data. An extension performance evaluation shows that, in the case of ensuring accurate clustering results, even if the analyst and individuals collude, the M-PPKS can prevent the disclosure of private information. © 2019 IEEE.

关键词： Internet of things

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Attack Intent Analysis Method Based on Attack Path Graph 2019

Attack Intent Analysis Method Based on Attack Path Graph

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Proceedings of the 2019 the 9th International Conference on Communication and Network Security

作者： Biqiong Chen Yanhua Liu Shijin Li Xiaoling Gao College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou Fujian China

ISBN: (纸本)9781450376624

关键词： Vulnerability key Asset Vulnerability Exploitation Attack Intention Attack Path Graph

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Research on Assistant Diagnostic Method of TCM Based on BERT

Research on Assistant Diagnostic Method of TCM Based on BERT

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IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Chuanjie Xu Feng Yuan Shouqiang Chen Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China School of Information Engineering Shandong Management University Jinan China Center of Hear of the Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine Jinan China

ISBN: (纸本)9781728194202

Traditional Chinese medicine (TCM) auxiliary diagnosis is a systematic diagnosis platform that uses computer modeling technology to assist TCM doctors in recording diseases, providing on time diagnoses, writing prescriptions, performing tele-medicine, and supporting medical teaching. This study proposes a Bidirectional Encoder Representations from Transformers TCM auxiliary diagnosis model using 20,000 items of TCM records. These records were collected from the outpatient clinic of the Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine. Specifically, our model aims to predict final diagnosis while taking TCM symptoms as inputs; for example, when we input relief of chest tightness but persistent tiredness and sluggishness, the model provides a diagnosis of chest paralysis. An experiment was conducted on these real-world Chinese medical data. Results show that our model achieves state-of-the-art performance. Hence, our proposed model can effectively use the information from the four diagnostic procedures in the TCM text.

关键词： Systematics Computational modeling Education Predictive models Writing Transformers Data models

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