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A hybrid biometric identification framework for high security applications

Frontiers of Computer science 2015年第3期9卷 392-401页

作者： Xuzhou LI Yilong YIN Yanbin NING Gongping YANG Lei PAN School of Computer Science and Technology Shandong University Jinan 250101 China Key Laboratory of Information Security and Intelligent Control of Shandong Province Shandong Youth University of Political Science Jinan 250103 China

Research on biometrics for high security applica- tions has not attracted as much attention as civilian or foren- sic applications. Limited research and deficient analysis so far has led to a lack of general solutions and leaves this as a challenging issue. This work provides a systematic analy- sis and identification of the problems to be solved in order to meet the performance requirements for high security applica- tions, a double low problem. A hybrid ensemble framework is proposed to solve this problem. Setting an adequately high threshold for each matcher can guarantee a zero false accep- tance rate （FAR） and then use the hybrid ensemble framework makes the false reject rate （FRR） as low as possible. Three ex- periments are performed to verify the effectiveness and gener- alization of the framework. First, two fingerprint verification algorithms are fused. In this test only 10.55% of fingerprints are falsely rejected with zero false acceptance rate, this is sig- nificantly lower than other state of the art methods. Second, in face verification, the framework also results in a large re- duction in incorrect classification. Finally, assessing the per- formance of the framework on a combination of face and gait verification using a heterogeneous database show this frame- work can achieve both 0% false rejection and 0% false accep- tance simultaneously.

关键词： biometric verification hybrid ensemble frame-work high security applications

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Handedness Recognition through Keystroke-Typing Behavior in Computer Forensics Analysis

Handedness Recognition through Keystroke-Typing Behavior in ...

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IEEE International Conference on Trust, security and Privacy in Computing and communications (TrustCom)

作者： Chao Shen Haodi Xu Haijun Wang Xiaohong Guan Science and Technology on Electronic Information Control Laboratory Chengdu China MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781509032068

Recognizing computer users' handedness provides important clues for profiling computer criminals in digital forensic analysis. Existing technologies for handedness recognition have two main problems that limit their applicability in the scenario of digital crimes: they can be intrusive, and they require costly equipment. Our solution is to infer users' handedness by analyzing keystroke-typing behavior. Field studies are first conducted to gather users' keystroke-typing data during their interaction with computers. Timing features are extracted to characterize users' typing rhythms, and the correlation between keystroke features and handedness is analyzed. Classification techniques are then developed for handedness recognition. Experimental results show that the handedness could be efficiently and accurately inferred from users' keystroke-typing behavior, with recognition rates expressed by the Area Under the ROC Curve (AUC) of 87.75%. To our knowledge, this is the first work that infers users' handedness based on their keystroke-typing biometric during interaction with computers, without dedicated and explicit actions that require attention from users.

关键词： Computers Feature extraction Forensics Speech recognition Fingerprint recognition Timing Bioinformatics

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Comment on “Quantum oblivious set-member decision protocol”

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Physical Review A 2016年第3期93卷 036301-036301页

作者： Bin Liu Di Xiao Wei Huang Ting-Ting Song Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) of Ministry of Education College of Computer Science Chongqing University Chongqing 400044 China Science and Technology on Communication Security Laboratory Chengdu 610041 China Department of Computer Science College of Information Science and Technology Jinan University Guangzhou 510632 China

In a recent paper [Phys. Rev. A 92, 022309 (2015)], the authors proposed a quantum oblivious set-member decision protocol, which is designed to allow a server to check whether a private secret of a user is a member of his private set in an oblivious manner. Such protocols should protect the privacies of both the server and the user. However, we find that the user in their protocol can steal l−1 bits of information about the server's private set by sending the false decoy states.

关键词： Quantum cryptography

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Network node importance measurement method based on vulnerability analysis 4th

Network node importance measurement method based on vulnerab...

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4th International Conference on Computer Engineering and Networks, CENet2014

作者： Li, Yahui Yang, Hongwa Xie, Kai Science and Technology on Communication Information Security Control Laboratory Jiaxing314000 China Northern Electronic Instrument Institute Beijing100191 China

ISBN: (纸本)9783319111032

As to select the important nodes from network, the key problems are to determine the basis and quantitative standard of evaluating node importance. This chapter proposes the measurement method of network node importance from the aspect of vulnerability, including topological structure vulnerability evaluation standard based on degree distribution, betweenness centrality, round-robin betweenness centrality, and extension degree distribution;and application vulnerability evaluation standard based on maximum load link and information value. The experiment results show that the measure standard of network node importance based on extension degree distribution not only reflects the value of the node itself, but comprehensively considers indirect effect of node to network;it can well describe the differences among nodes in a network, and time complexity of the algorithm is smaller. © Springer International Publishing Switzerland 2015.

关键词： Topology

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Fluctuating Power Logic (FPL): A constructive SCA resistant scheme at transistor level

Fluctuating Power Logic (FPL): A constructive SCA resistant ...

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2016年密码芯片学术会议

作者： Fan Zhang Liang Geng Congyuan Xu Jizhong Shen Xinjie Zhao Shize Guo College of Information Science & Electronic Engineering Zhejiang UniversityHangzhou 310027 China College of Information Science & Electronic Engineering Zhejiang UniversityHangzhou 310027 China Science and Technology on Communication Security Laboratory Chengdu 610041China The Institute of North Electronic Equipment Beijing 100000 China

Hiding and masking are two mainstream countermeasures against side channel analysis (SCA) at cell *** power analysis, both rely on the fact that variant data transitions consume more distinguishable power than invariant *** this letter, we propose a novel scheme based on fluctuating power logic (FPL), which mitigates the side-channel effect by employing cascade voltage logic to fluctuate physical power *** proposed scheme is illustrated by a standard flip-flop which typically behaves as a major power consumer of the *** based simulation shows that the modified flip-flop is resistant against power analysis at the cost of doubled power *** proposal can be further applied to enhance various SCA-resistant logics, such as sense-amplifier based logic (SABL) and wave dynamic differential logic (WDDL).

关键词： low power flip-flop clock-gating scheme dual-edge

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Markov chain-based attack on the CSMA/CA mechanism

Markov chain-based attack on the CSMA/CA mechanism

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International Conference on Multimedia, communication and Computing Application, MCCA 2014

作者： Wang, W. Zhao, W.H. Science and Technology on Communication Information Security Control Laboratory JiaxingZhejiang China Jiangnan Electronic Communication Institute JiaxingZhejiang314001 China Nanhu College Jiaxing University Jiaxing China

ISBN: (纸本)9781138027756

The CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) mechanism is formally modeled first. Then, based on the Markov Chain theory, the analysis of the attack on CSMA/CA is introduced from two aspects which are the stochastic performance model and bandwidth share model. After discussing the typical attack methods, the performance is analyzed from the aspects of throughput, communication efficiency, and collision numbers, which validates the feasibility and efficiency of attack method based on Markov Chain theory. © 2015 Taylor & Francis Group, London.

关键词： Carrier sense multiple access

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BLIND CFO ESTIMATION FOR MULTIUSER OFDM UPLINK WITH LARGE NUMBER OF RECEIVE ANTENNAS

BLIND CFO ESTIMATION FOR MULTIUSER OFDM UPLINK WITH LARGE NU...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Weile Zhang Feifei Gao Bobin Yao MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University China Tsinghua National Laboratory for Information Science and Technology Tsinghua University China School of Electronic and Control Engineering Chang'an University China

ISBN: (纸本)9781479999897

In this paper, we propose a new blind carrier frequency offset (CFO) estimation method for multiuser orthogonal frequency division multiplexing (OFDM) uplink transmissions. The spatial multiplexing is supported in the considered model that allows the subcarriers to be simultaneously occupied by multiple users. We propose to assign different null subcarriers to different users and design algorithm that can perform blind CFO estimation for each individual user with the aid of large number of receive antennas, which then removes the necessity of multidimensional searching. Numerical results are provided to corroborate the proposed studies.

关键词： Multiuser CFO estimation OFDM large number of antennas

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Trust recommendation algorithm for the virtual community based Internet of Things(IoT)

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Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University 2015年第2期42卷 52-57and179页

作者： Guo, Jingjing Ma, Jianfeng School of Computer Science and Technology Xidian Univ. Xi'an710071 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

In available trust based recommendation schemes, users always tend to transact with the entity with the highest trust value, which will result in the fact that the virtual community's resource cannot be fully utilized. The entity with the highest trust value will also delay the response because of its capacity constraint, so that its trust value will be bound to decline. To resolve this problem, we propose a recommendation algorithm which takes the community benefit and the stability of the entities' trust value into account. The community's control center adopts the Lyapunov optimization method to make a decision which can give it the maximum benefit on the premise of satisfying the desired constraint of the interaction requester, meanwhile guaranteeing the stability of the community nodes' trust value. Theoretical analysis and experiments show that our algorithm can stabilize the community nodes' trust value, and that it also can enable the whole community and resource requester to get more benefits. ©, 2015, science Press. All right reserved.

关键词： Network security

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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