Literatura académica sobre el tema "Mathematical data- Security"
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Artículos de revistas sobre el tema "Mathematical data- Security"
Nurhidayati, Rika y Salauddin Muis. "Analysis Of Voice Data Security Security By Using The Rc4 Algorithm". Jurnal Info Sains : Informatika dan Sains 11, n.º 2 (1 de septiembre de 2021): 22–28. http://dx.doi.org/10.54209/infosains.v11i2.44.
Texto completoErkayev, Husan Ahmadaliyevich. "MATHEMATICAL MODEL OF CRYPTOGRAPHICAL HISTORICAL CODE ALGORITHMS TO DATA SECURITY." Theoretical & Applied Science 89, n.º 09 (30 de septiembre de 2020): 30–33. http://dx.doi.org/10.15863/tas.2020.09.89.8.
Texto completoSaksonov, E. A. "Method of Depersonalization of Personal Data". INFORMACIONNYE TEHNOLOGII 27, n.º 6 (9 de junio de 2021): 314–21. http://dx.doi.org/10.17587/it.27.314-321.
Texto completoHub, Miloslav y Agnès Kateřina Příhodová. "Impact of Globalisation on Data Security – Authentication Issues". SHS Web of Conferences 92 (2021): 05009. http://dx.doi.org/10.1051/shsconf/20219205009.
Texto completoHorubała, Aleksandra, Daniel Waszkiewicz, Michał Andrzejczak y Piotr Sapiecha. "Data confidentiality and computations hiding in cloud services for public administration". Computer Science and Mathematical Modelling, n.º 7/2018 (18 de julio de 2018): 11–18. http://dx.doi.org/10.5604/01.3001.0012.2001.
Texto completoBolshakov, A. S., A. I. Zhila y A. V. Osin. "FUZZY LOGIC DATA PROTECTION MANAGEMENT". H&ES Research 13, n.º 4 (2021): 37–47. http://dx.doi.org/10.36724/2409-5419-2021-13-4-37-47.
Texto completoHenge, Santosh Kumar, Gitanjali Jayaraman, M. Sreedevi, R. Rajakumar, Mamoon Rashid, Sultan S. Alshamrani, Mrim M. Alnfiai y Ahmed Saeed AlGhamdi. "Secure keys data distribution based user-storage-transit server authentication process model using mathematical post-quantum cryptography methodology". Networks and Heterogeneous Media 18, n.º 3 (2023): 1313–34. http://dx.doi.org/10.3934/nhm.2023057.
Texto completoRaj, A. Samson Arun, R. Venkatesan, S. Malathi, V. D. Ambeth Kumar, E. Thenmozhi, Anbarasu Dhandapani, M. Ashok Kumar y B. Chitra. "A Mathematical Queuing Model Analysis Using Secure Data Authentication Framework for Modern Healthcare Applications". Journal of Sensors 2022 (16 de septiembre de 2022): 1–15. http://dx.doi.org/10.1155/2022/8397635.
Texto completoLiu, Yutang y Qin Zhang. "Mathematical Modeling of Static Data Attribute Encryption Based on Big Data Technology". Journal of Function Spaces 2022 (2 de agosto de 2022): 1–10. http://dx.doi.org/10.1155/2022/4292063.
Texto completoBoychenko, O. V. y D. V. Ivanyuta. "INFORMATION SECURITY MODELS". Construction economic and environmental management 80, n.º 3 (2022): 33–39. http://dx.doi.org/10.37279/2519-4453-2021-3-33-39.
Texto completoTesis sobre el tema "Mathematical data- Security"
Ma, Chunyan. "Mathematical security models for multi-agent distributed systems". CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2568.
Texto completoAtoui, Ibrahim Abdelhalim. "Data reduction techniques for wireless sensor networks using mathematical models". Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD009.
Texto completoIn this thesis, we present energy-efficient data reduction and security techniques dedicated for wireless sensor networks. First, we propose a data aggregation model based on the similarity function that helps in removing the redundant data. In addition, based on the fitting functions we worked on sending less data features, accompanied with the fitting function that expresses all features. Second, we focus on heterogeneity of the data while studying the correlation among these multivariate features in order to enhance the data prediction technique that is based on the polynomial function, all after removing the similar measures in the aggregation phase using the Euclidean distance. Finally, we provide a rigorous security framework inherited from cryptography satisfies the level of exigence usually attained in tree-based WSNs. It prevents attackers from gaining any information about sensed data, by ensuring an end-to-end privacy between sensor nodes and the sink. In order to validate our proposed techniques, we implemented the simulations of the first technique on real readings collected from a small Sensor Scope network which is deployed at the Grand-St-Bernard, while the simulations of the second and the third techniques are conducted on real data collected from 54 sensors deployed in the Intel Berkeley Research Lab. The performance of our techniques is evaluated according to data reduction rate, energy consumption, data accuracy and time complexity
Sathisan, Shashi Kumar. "Encapsulation of large scale policy assisting computer models". Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/101261.
Texto completoM.S.
Alkadi, Alaa. "Anomaly Detection in RFID Networks". UNF Digital Commons, 2017. https://digitalcommons.unf.edu/etd/768.
Texto completoLi, Jianzhou y University of Lethbridge Faculty of Arts and Science. "Design of a novel hybrid cryptographic processor". Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2005, 2005. http://hdl.handle.net/10133/266.
Texto completoviii, 87 leaves : ill. (some col.) ; 28 cm.
Li, Ling Feng. "An image encryption system based on two-dimensional quantum random walks". Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950660.
Texto completoTerashima, Robert Seth. "Tweakable Ciphers: Constructions and Applications". PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2484.
Texto completoHaraldsson, Emil. "Strong user authentication mechanisms". Thesis, Linköping University, Department of Electrical Engineering, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2688.
Texto completoFor Siemens Industrial Turbomachinery to meet its business objectives a modular authentication concept has to be implemented. Such a mechanism must be cost- effective while providing a well-balanced level of security, easy maintenance and be as user-friendly as possible.
Authenticating users securely involves the combination of two fields, theory of authentication mechanisms in information systems and human computer interaction. To construct a strong user authentication system the correlations of these fields has to be understood and provide guidance in the design.
Strong user authentication mechanisms enforce the use of two-factor authentication or more. The combinations implemented rely on knowledge, possession and sometimes logical-location.
A user authentication system has been implemented using leading industrial products as building blocks glued together with security analysis, programming and usability research.
The thesis is divided into two parts, the first part giving the theoretical background of cryptography, authentication theory and protocols needed for the understanding of the second part, providing security analysis, blueprints, and detailed discussions on the implemented system.
Conclusions have been drawn regarding the implemented system and its context as well as from strict theoretical reasoning regarding the authentication field in general. Conclusions include:
· The unsuitability of remote authentication using biometrics
· The critical importance of client security in remote authentication
· The importance of a modular structure for the security of complex network-based systems
Huang, Jian. "FPGA Implementations of Elliptic Curve Cryptography and Tate Pairing over Binary Field". Thesis, University of North Texas, 2007. https://digital.library.unt.edu/ark:/67531/metadc3963/.
Texto completoFriot, Nicolas. "Itérations chaotiques pour la sécurité de l'information dissimulée". Thesis, Besançon, 2014. http://www.theses.fr/2014BESA2035/document.
Texto completoDiscrete dynamical systems by chaotic or asynchronous iterations have proved to be highly interesting toolsin the field of computer security, thanks to their unpredictible behavior obtained under some conditions. Moreprecisely, these chaotic iterations possess the property of topological chaos and can be programmed in anefficient way. In the state of the art, they have turned out to be really interesting to use notably through digitalwatermarking schemes. However, despite their multiple advantages, these existing algorithms have revealedsome limitations. So, these PhD thesis aims at removing these constraints, proposing new processes whichcan be applied both in the field of digital watermarking and of steganography. We have studied these newschemes on two aspects: the topological security and the security based on a probabilistic approach. Theanalysis of their respective security level has allowed to achieve a comparison with the other existing processessuch as, for example, the spread spectrum. Application tests have also been conducted to steganalyse and toevaluate the robustness of the algorithms studied in this PhD thesis. Thanks to the obtained results, it has beenpossible to determine the best adequation of each processes with targeted application fields as, for example,the anonymity on the Internet, the contribution to the development of the semantic web, or their use for theprotection of digital documents. In parallel to these scientific research works, several valorization perspectiveshave been proposed, aiming at creating a company of innovative technology
Libros sobre el tema "Mathematical data- Security"
Kopczuk, Wojciech. Uncovering the American dream: Inequality and mobility in social security earnings data since 1937. Cambridge, Mass: National Bureau of Economic Research, 2007.
Buscar texto completoKopczuk, Wojciech. Uncovering the american dream: Inequality and mobility in social security earnings data since 1937. Cambridge, MA: National Bureau of Economic Research, 2007.
Buscar texto completoÖzyer, Tansel. Mining Social Networks and Security Informatics. Dordrecht: Springer Netherlands, 2013.
Buscar texto completoBrand, Ruth. Anonymität von Betriebsdaten: Verfahren zur Erfassung und Massnahmen zur Verringerung des Reidentifikationsrisikos. Nürnberg: Institut für Arbeitsmarkt- und Berufsforschung der Bundesanstalt für Arbeit, 2000.
Buscar texto completoIgor, Kotenko y Skormin Victor A. 1946-, eds. Computer network security: 6th international conference on mathematical methods, models and architectures for computer network security, MMM-ACNS 2012, St. Petersburg, Russia, October 17-19, 2012 : proceedings. Heidelberg: Springer, 2012.
Buscar texto completoDiergardt, Martin. Modeling scenarios for analyzing the risks of complex computer based information systems. Berlin: dissertation.de, 2007.
Buscar texto completoKott, Alexander. Estimating Impact: A Handbook of Computational Methods and Models for Anticipating Economic, Social, Political and Security Effects in International Interventions. Boston, MA: Springer Science+Business Media, LLC, 2010.
Buscar texto completoTorra, Vicenç. Modeling Decisions for Artificial Intelligence: 9th International Conference, MDAI 2012, Girona, Catalonia, Spain, November 21-23, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Buscar texto completoAggarwal, Charu C. Outlier Analysis. New York, NY: Springer New York, 2013.
Buscar texto completoAmy, Felty y SpringerLink (Online service), eds. Interactive Theorem Proving: Third International Conference, ITP 2012, Princeton, NJ, USA, August 13-15, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Buscar texto completoCapítulos de libros sobre el tema "Mathematical data- Security"
Tiwari, Shiv Kumar, Deepak Singh Rajput, Saurabh Sharma, Subhrendu Guha Neogi y Ashish Mishra. "Cloud Virtual Image Security for Medical Data Processing". En Mathematical Modeling and Soft Computing in Epidemiology, 317–45. First edition. | Boca Raton, FL : CRC Press, 2021. |: CRC Press, 2020. http://dx.doi.org/10.1201/9781003038399-17.
Texto completoKelley, Patrick Gage, Saranga Komanduri, Michelle L. Mazurek, Richard Shay, Timothy Vidas, Lujo Bauer, Nicolas Christin y Lorrie Faith Cranor. "The Impact of Length and Mathematical Operators on the Usability and Security of System-Assigned One-Time PINs". En Financial Cryptography and Data Security, 34–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41320-9_3.
Texto completoNorem, Savannah, Ashley E. Rice, Samantha Erwin, Robert A. Bridges, Sean Oesch y Brian Weber. "A Mathematical Framework for Evaluation of SOAR Tools with Limited Survey Data". En Computer Security. ESORICS 2021 International Workshops, 557–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95484-0_32.
Texto completoArki, Oussama y Abdelhafid Zitouni. "A Security Framework for Cloud Data Storage(CDS) Based on Agent". En Applied Computational Intelligence and Mathematical Methods, 62–73. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67621-0_6.
Texto completoRajput, Deepak Singh, Saurabh Sharma, Shiv Kumar Tiwari, A. K. Upadhyay y Ashish Mishra. "Medical Data Security Using Blockchain and Machine Learning in Cloud Computing". En Mathematical Modeling and Soft Computing in Epidemiology, 347–74. First edition. | Boca Raton, FL : CRC Press, 2021. |: CRC Press, 2020. http://dx.doi.org/10.1201/9781003038399-18.
Texto completoGanguli, Runa, Priyanka Banerjee, Sanjib Halder y Soumya Sen. "A Mathematical Recommendation Model to Rank Reviewers Based on Weighted Score for Online Review System". En Emerging Technologies in Data Mining and Information Security, 317–25. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9774-9_31.
Texto completoMa, Xiaoxiao. "Fitting Approximation Algorithm for Applied Mathematical Model". En The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, 443–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89511-2_57.
Texto completoHan, Bingbing y Zaixing Su. "Mathematical Model of Network Center Data Hierarchical Encryption Based on Decentralization". En The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, 1010–17. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89508-2_131.
Texto completoHao, Peng. "Research on Mathematical Modeling Optimization of Recognition Algorithm Based on Multi Feature Extraction". En The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, 214–19. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89511-2_26.
Texto completoKostyuchenko, Yuriy V., Maxim Yuschenko y Ivan Kopachevsky. "Stochastic Approaches to Analysis and Modeling of Multi-Sources and Big Data in Tasks of Homeland Security: Socio-Economic and Socio-Ecological Crisis Control Tools". En Advanced Mathematical Techniques in Science and Engineering, 57–99. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003337034-3.
Texto completoActas de conferencias sobre el tema "Mathematical data- Security"
Kuznetsova, Nataliya M., Tatyana V. Karlova, Alexander Y. Bekmeshov, Elena A. Kirillova, Marianna V. Mikhaylova y Andrey V. Averchenkov. "Mathematical and Algorithmic Prevention of Biometric Data Leaks". En 2021 International Conference on Quality Management, Transport and Information Security, Information Technologies (IT&QM&IS). IEEE, 2021. http://dx.doi.org/10.1109/itqmis53292.2021.9642819.
Texto completoJaenisch, Holger M., James W. Handley y Michael L. Hicklen. "Data model predictive control as a new mathematical framework for simulation and VV&A". En Defense and Security Symposium, editado por Kevin L. Priddy y Emre Ertin. SPIE, 2006. http://dx.doi.org/10.1117/12.666466.
Texto completoJaenisch, Holger M., James W. Handley, Jeffery P. Faucheux y Kenneth Lamkin. "A novel application of data modeling for extracting mathematical ontologies and relationship matrix features from text documents". En Defense and Security, editado por Dawn A. Trevisani y Alex F. Sisti. SPIE, 2005. http://dx.doi.org/10.1117/12.626666.
Texto completoLaine, Trevor I. y Kenneth W. Bauer, Jr. "A mathematical framework for the optimization of rejection and ROC thresholds in the fusion of correlated sensor data". En Defense and Security, editado por Belur V. Dasarathy. SPIE, 2004. http://dx.doi.org/10.1117/12.542331.
Texto completoBansal, Malti, Varun Sirpal, Tanmaya Jain, Ujjwal y Uma Nangia. "Enhancing medical data security using tiny encryption algorithm and least significant bit steganography". En CONFERENCE ON MATHEMATICAL SCIENCES AND APPLICATIONS IN ENGINEERING: CMSAE-2021. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0149166.
Texto completoDinicu, Anca y Romana Oancea. "PREDICTABILITY POSSIBILITIES BASED ON MATHEMATICAL MODELS OF CONFLICT SITUATIONS". En eLSE 2014. Editura Universitatii Nationale de Aparare "Carol I", 2014. http://dx.doi.org/10.12753/2066-026x-14-073.
Texto completoRamalingam, Hariharan y V. Prasanna Venkatesan. "Introspection of Availability in Service Based Smart Systems Using Internet of Things (IoT)". En International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-3bj8t2.
Texto completoDjurupova, Bermet, Jusup Pirimbaev y Gulmira Samatova. "Nutrition Problems in the Kyrgyz Republic and the Ways of Their Solution". En International Conference on Eurasian Economies. Eurasian Economists Association, 2019. http://dx.doi.org/10.36880/c11.02244.
Texto completoPandey, Kartikey y Deepmala Sharma. "Advances in data security through elliptical curve cryptography". En RECENT TRENDS IN APPLIED MATHEMATICS IN SCIENCE AND ENGINEERING. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0145107.
Texto completoSherin, D. A. Angel, V. Maheswari y V. Balaji. "Securing data using injective labeling on acyclic graphs". En 2ND INTERNATIONAL CONFERENCE ON MATHEMATICAL TECHNIQUES AND APPLICATIONS: ICMTA2021. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0108507.
Texto completoInformes sobre el tema "Mathematical data- Security"
Semerikov, Serhiy, Illia Teplytskyi, Yuliia Yechkalo, Oksana Markova, Vladimir Soloviev y Arnold Kiv. Computer Simulation of Neural Networks Using Spreadsheets: Dr. Anderson, Welcome Back. [б. в.], junio de 2019. http://dx.doi.org/10.31812/123456789/3178.
Texto completoData Encryption Standard. Gaithersburg, MD: National Institute of Standards and Technology, 1988. http://dx.doi.org/10.6028/nist.fips.46-1.
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