检索结果-内蒙古大学图书馆

作者： Lv, Chen Jiang, Wei Hu, Songlin Wang, Jiye Lu, Guoliang Liu, Zhiyong School of Information Science and Engineering Shandong Normal University China Greatwall Drilling Company R&D Academy of Well Logging CNPC Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China Department of Information Technology State Grid Corporation of China Beijing China School of Mechanical Engineering Shandong University China Institute of Computing Technology Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China

Current QoS-aware automatic service composition queries over a network of web services are often one-time in nature. After a network of web services is built, such queries are issued once, and answers are found from the scratch. The underlying assumption is that the participating web services are rather static, which means that their functional and non-functional parameters seldom change. However, such an assumption is often baseless. New services come and go, service APIs change gradually, and QoS values fluctuate in practice. Therefore, a support for efficiently adapting service composition is desired. In this paper, we propose an event driven continuous query algorithm to intelligently cope with different types of dynamic services, and thus enable evolution of service composition. Evaluation using both real QoS data and synthetic web service data shows its superior performance, compared with the state-of-the-art solution which won the performance championship of Web Service Challenge in 2009 and 2010. Moreover, we generalize a new graph problem: dynamic single-source optimal-Directed Acyclic Graphs (DAG) problem based on the above work. It is argued that API recommendation for framework evolution, as another typical application, could also be modeled and addressed efficiently using the proposed new graph approach. © 2017 IEEE.

关键词： Web services

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Common Limitations of Image Processing Metrics: A Picture Story

arXiv

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arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

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A Protective Mechanism for the Access Control System in the Virtual Domain

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China Communications 2016年第11期13卷 129-142页

作者： Jinan Shen Deqing Zou Hai Jin Kai Yang Bin Yuan Weiming Li Services Computing Technology and System Laboratory Cluster and Grid Computing LaboratorySchool of Computing Science and TechnologyHuazhong University of Science and Technology School of Information Engineering Hubei University for Nationalities

In traditional framework,mandatory access control(MAC) system and malicious software are run in kernel mode. Malicious software can stop MAC systems to be started and make it do invalid. This problem cannot be solved under the traditional framework if the operating system(OS) is comprised since malwares are running in ring 0 level. In this paper,we propose a novel way to use hypervisors to protect kernel integrity and the access control system in commodity operating systems. We separate the access control system into three parts: policy management(PM),security server(SS) and policy enforcement(PE). Policy management and the security server reside in the security domain to protect them against malware and the isolation feather of the hypervisor can protect them from attacks. We add an access vector cache(AVC) between SS and PE in the guest OS,in order to speed up communication between the guest OS and the security domain. The policy enforcement module is retained in the guest OS for performance. The security of AVC and PE can be ensured by using a memory protection mechanism. The goal of protecting the OS kernel is to ensure the security of the execution path. We implementthe system by a modified Xen hypervisor. The result shows that we can secure the security of the access control system in the guest OS with no overhead compared with modules in the latter. Our system offers a centralized security policy for virtual domains in virtual machine ***: hypervisor; virtualization; memo-

关键词： hypervisor virtualization memory protection guest OS access control system

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Theory and methodology of research on cloud security

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science China(Information sciences) 2016年第5期59卷 15-17页

作者： Hai JIN Weiqi DAI Deqing ZOU Services Computing Technology and System Lab Big Data Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

Cloud computing is a model for enabling ubiquitous,convenient,on-demand access to a shared pool of configurable computing *** to Gartner’s survey,cloud computing has been at the head of a list of the top ten IT strategic technologies for some *** computing is currently undergoing vigorous development and promotion by many leading Chinese and foreign enterprises,and it has become the basis for a new

关键词： TPM Theory and methodology of research on cloud security

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UiLog： Improving Log-Based Fault Diagnosis by Log Analysis

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Journal of computer science & technology 2016年第5期31卷 1038-1052页

作者： De-Qing Zou Services Computing Technology and System Laboratory Huazhong University of Science and Technology Wuhan ~3007~ China Big Data Technology and System Laboratory Huazhong University of Science and Technology Wuhan 430074 China Cluster and Grid Computing Laboratory Huazhong University of Science and Technology Wuhan 430074 China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

In modern computer systems, system event logs have always been the primary source for checking system status. As computer systems become more and more complex, the interaction between software and hardware increases frequently. The components will generate enormous log information, including running reports and fault information. The sheer quantity of data is a great challenge for analysis relying on the manual method. In this paper, we implement a management and analysis system of log information, which can assist system administrators to understand the real-time status of the entire system, classify logs into different fault types, and determine the root cause of the faults. In addition, we improve the existing fault correlation analysis method based on the results of system log classification. We apply the system in a cloud computing environment for evaluation. The results show that our system can classify fault logs automatically and effectively. With the proposed system, administrators can easily detect the root cause of faults.

关键词： fault diagnosis system event log log classification fault correlation analysis

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Exploring the Impact of Processing Guarantees on Performance of Stream Data Processing

Exploring the Impact of Processing Guarantees on Performance...

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2017 17th IEEE International Conference on Communication technology (ICCT 2017)

作者： Syed Muhammad Abrar Akber Changfu Lin Hanhua Chen Fan Zhang Hai Jin Cluster and Grid Computing Lab Services Computing Technology and System Lab Big Data Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology

Processing semantics ensure tuple processing guarantees during system recovery from failures. It determines whether particular tuples are re-processed or not upon system recovery. Processing semantics facilitate to maintain real-time response as well as correctness of results in stream data processing. Existing literature is in real deficit to provide sufficient resources exclusively on processing semantics. This work focuses on reviewing processing semantics in stream data processing *** article aims at exploring the impact of processing guaran-tees on performance of stream data processing. We summarize current research directions to guarantee processing semantics,based on prominent stream processing engines. Furthermore,we compare throughput for a couple of representative stream processing engines under all possible processing *** experiments show that at-most once processing guarantee provides the highest throughput among other guarantees. Lastly,challenges for further research are also discussed in this paper.

关键词： stream data processing processing semantic processing guarantee at-least once at-most once exactly-once

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A survey of cloud resource management for complex engineering applications

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Frontiers of computer science 2016年第3期10卷 447-461页

作者： Haibao CHEN Song WU Hai JIN Wenguang CHEN Jidong ZHAI Yingwei LUO Xiaolin WANG Services Computing Technology and System Lab Cluster and Grid Computing LabSchool of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Institute of High Performance Computing Tsinghua University Beijing 100084 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China School of Computer and Information Engineering Chuzhou University Chuzhou 239000 China

Traditionally, complex engineering applications （CEAs）, which consist of numerous components （software） and require a large amount of computing resources, usu- ally run in dedicated clusters or high performance computing （HPC） centers. Nowadays, Cloud computing system with the ability of providing massive computing resources and cus- tomizable execution environment is becoming an attractive option for CEAs. As a new type on Cloud applications, CEA also brings the challenges of dealing with Cloud resources. In this paper, we provide a comprehensive survey of Cloud resource management research for CEAs. The survey puts forward two important questions： 1） what are the main chal- lenges for CEAs to run in Clouds？ and 2） what are the prior research topics addressing these challenges？ We summarize and highlight the main challenges and prior research topics. Our work can be probably helpful to those scientists and en- gineers who are interested in running CEAs in Cloud envi- ronment.

关键词： Cloud computing complex engineering application resource management virtualization

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SPT clusters with DES and HST weak lensing. II. Cosmological constraints from the abundance of massive halos

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Physical Review D 2024年第8期110卷 083510页

作者： S. Bocquet S. Grandis L. E. Bleem M. Klein J. J. Mohr T. Schrabback T. M. C. Abbott P. A. R. Ade M. Aguena A. Alarcon S. Allam S. W. Allen O. Alves A. Amon A. J. Anderson J. Annis B. Ansarinejad J. E. Austermann S. Avila D. Bacon M. Bayliss J. A. Beall K. Bechtol M. R. Becker A. N. Bender B. A. Benson G. M. Bernstein S. Bhargava F. Bianchini M. Brodwin D. Brooks L. Bryant A. Campos R. E. A. Canning J. E. Carlstrom A. Carnero Rosell M. Carrasco Kind J. Carretero F. J. Castander R. Cawthon C. L. Chang C. Chang P. Chaubal R. Chen H. C. Chiang A. Choi T-L. Chou R. Citron C. Corbett Moran J. Cordero M. Costanzi T. M. Crawford A. T. Crites L. N. da Costa M. E. S. Pereira C. Davis T. M. Davis J. DeRose S. Desai T. de Haan H. T. Diehl M. A. Dobbs S. Dodelson C. Doux A. Drlica-Wagner K. Eckert J. Elvin-Poole S. Everett W. Everett I. Ferrero A. Ferté A. M. Flores J. Frieman J. Gallicchio J. García-Bellido M. Gatti E. M. George G. Giannini M. D. Gladders D. Gruen R. A. Gruendl N. Gupta G. Gutierrez N. W. Halverson I. Harrison W. G. Hartley K. Herner S. R. Hinton G. P. Holder D. L. Hollowood W. L. Holzapfel K. Honscheid J. D. Hrubes N. Huang J. Hubmayr E. M. Huff D. Huterer K. D. Irwin D. J. James M. Jarvis G. Khullar K. Kim L. Knox R. Kraft E. Krause K. Kuehn N. Kuropatkin F. Kéruzoré O. Lahav A. T. Lee P.-F. Leget D. Li H. Lin A. Lowitz N. MacCrann G. Mahler A. Mantz J. L. Marshall J. McCullough M. McDonald J. J. McMahon J. Mena-Fernández F. Menanteau S. S. Meyer R. Miquel J. Montgomery J. Myles T. Natoli A. Navarro-Alsina J. P. Nibarger G. I. Noble V. Novosad R. L. C. Ogando Y. Omori S. Padin S. Pandey P. Paschos S. Patil A. Pieres A. A. Plazas Malagón A. Porredon J. Prat C. Pryke M. Raveri C. L. Reichardt J. Roberson R. P. Rollins C. Romero A. Roodman J. E. Ruhl E. S. Rykoff B. R. Saliwanchik L. Salvati C. Sánchez E. Sanchez D. Sanchez Cid A. Saro K. K. Schaffer L. F. Secco I. Sevilla-Noarbe K. Sharon E. Sheldon T. Shin C. Sievers G. Smecher M. Smith T. Somboonpanyakul M. Sommer B. Stalder A. A. Stark J. Stephen V. Straz University Observatory Faculty of Physics Universität Innsbruck Institut für Astro- und Teilchenphysik Technikerstraße 25/8 6020 Innsbruck Austria High-Energy Physics Division Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Max Planck Institute for Extraterrestrial Physics Gießenbachstraße 1 85748 Garching Germany Argelander-Institut für Astronomie Auf dem Hügel 71 53121 Bonn Germany Cerro Tololo Inter-American Observatory NSF’s National Optical-Infrared Astronomy Research Laboratory Casilla 603 La Serena Chile School of Physics and Astronomy Cardiff University Cardiff CF24 3YB United Kingdom Laboratório Interinstitucional de e-Astronomia—LIneA Rua Gal. José Cristino 77 Rio de Janeiro Rio de Janeiro—20921-400 Brazil Fermi National Accelerator Laboratory P. O. Box 500 Batavia Illinois 60510 USA Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall Stanford California 94305 USA Department of Physics Stanford University 382 Via Pueblo Mall Stanford California 94305 USA SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park California 94025 USA Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Institute of Astronomy University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom School of Physics University of Melbourne Parkville Victoria 3010 Australia NIST Quantum Devices Group 325 Broadway Mailcode 817.03 Boulder Colorado 80305 USA Department of Physics University of Colorado Boulder Colorado 80309 USA Institut de Física d’Altes Energies (IFAE) The Barcelona Institute of Science and Technology Campus UAB 08193 Bellaterra (Barcelona) Spain Institute of Cosmology and Gravitation University of Portsmouth Portsmouth

We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range 0.25–1.78 over a total sky area of 5200 deg2. We use DES Year 3 weak-lensing data for 688 clusters with redshifts z<0.95 and HST weak-lensing data for 39 clusters with 0.6clusters and allow us to empirically constrain the SZ observable-mass relation without having to make strong assumptions about, e.g., the hydrodynamical state of the clusters. For a flat ΛCDM cosmology, and marginalizing over the sum of massive neutrinos, we measure Ωm=0.286±0.032, σ8=0.817±0.026, and the parameter combination σ8(Ωm/0.3)0.25=0.805±0.016. Our measurement of S8≡σ8Ωm/0.3=0.795±0.029 and the constraint from Planck CMB anisotropies (2018 TT, TE, EE+lowE) differ by 1.1σ. In combination with that Planck dataset, we place a 95% upper limit on the sum of neutrino masses ∑mν<0.18 eV. When additionally allowing the dark energy equation of state parameter w to vary, we obtain w=−1.45±0.31 from our cluster-based analysis. In combination with Planck data, we measure w=−1.34−0.15+0.22, or a 2.2σ difference with a cosmological constant. We use the cluster abundance to measure σ8 in five redshift bins between 0.25 and 1.8, and we find the results to be consistent with structure growth as predicted by the ΛCDM model fit to Planck primary CMB data.

关键词： Cosmological parameters Dark energy Large scale structure of the Universe Galaxy clusters

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Erratum to: Search for exclusive Higgs and Z boson decays to ϕγ and ργ with the ATLAS detector

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Journal of High Energy Physics 2023年第12期2023卷 1-21页

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Afik, Y. Agatonovic-Jovin, T. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Alberghi, G. L. Albert, J. Albicocco, P. Alconada Verzini, M. J. Alderweireldt, S. C. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A. V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D. J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Araujo Ferraz, V. Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baas, A. E. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Bakker, P. J. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Bandyopadhyay, A. Banerjee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisits, M.-S. Barkeloo, J. T. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barno Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States of America Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz United States of America Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene United States of America Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas – LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston United States of America Joi

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Corrigendum to “Fine-Grained Control-Flow Integrity Based on Points-to Analysis for CPS”

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Security and Communication Networks 2018年第1期2018卷

作者： Weizhong Qiang Shizhen Wang Hai Jin Jiangying Zhong Services Computing Technology and System Lab Cluster and Grid Computing Lab Big Data Security Engineering Research Center School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 ***

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