Literatura académica sobre el tema "Secure classification"
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Artículos de revistas sobre el tema "Secure classification"
Pearson, Jane L., Deborah A. Cohn, Philip A. Cowan y Carolyn Pape Cowan. "Earned- and continuous-security in adult attachment: Relation to depressive symptomatology and parenting style". Development and Psychopathology 6, n.º 2 (1994): 359–73. http://dx.doi.org/10.1017/s0954579400004636.
Texto completoHareesha, K. S. y M. Sumana. "Secure Two Party Privacy Preserving Classification Using Encryption". International Journal of Information and Electronics Engineering 6, n.º 2 (2016): 67–71. http://dx.doi.org/10.18178/ijiee.2016.6.2.597.
Texto completoBaars, Thijs y Marco Spruit. "Designing a Secure Cloud Architecture". International Journal of Information Security and Privacy 6, n.º 1 (enero de 2012): 14–32. http://dx.doi.org/10.4018/jisp.2012010102.
Texto completoT., Tamanna y Rajeev Kumar. "Secure Cloud Model using Classification and Cryptography". International Journal of Computer Applications 159, n.º 6 (15 de febrero de 2017): 8–13. http://dx.doi.org/10.5120/ijca2017912953.
Texto completoUsharani, A. V. y Girija Attigeri. "Secure EMR Classification and Deduplication Using MapReduce". IEEE Access 10 (2022): 34404–14. http://dx.doi.org/10.1109/access.2022.3161439.
Texto completoWiseman, Simon R. "Classification services in the SWORD secure DBMS". Computers & Security 14, n.º 4 (enero de 1995): 307–21. http://dx.doi.org/10.1016/0167-4048(95)00004-r.
Texto completoSalehi, Mahmood y Azzedine Boukerche. "Secure opportunistic routing protocols: methods, models, and classification". Wireless Networks 25, n.º 2 (11 de septiembre de 2017): 559–71. http://dx.doi.org/10.1007/s11276-017-1575-1.
Texto completo., S. Narayanan. "CLASSIFICATION OF SECURE ENCRYPTED RELATIONALDATA IN CLOUD COMPUTING". International Journal of Research in Engineering and Technology 05, n.º 03 (25 de marzo de 2016): 159–66. http://dx.doi.org/10.15623/ijret.2016.0503034.
Texto completoS L Swapna y V Saravanan. "Jaccard Index Cat Gradient Boosting Classification for Secured Big Data Communication". Applied Science and Engineering Journal for Advanced Research 1, n.º 5 (30 de septiembre de 2022): 1–14. http://dx.doi.org/10.54741/asejar.1.5.1.
Texto completoB, Murugeshwari, Jayakumar C y Sarukesi K. "Secure Multi Party Computation Technique for Classification Rule Sharing". International Journal of Computer Applications 55, n.º 7 (20 de octubre de 2012): 1–10. http://dx.doi.org/10.5120/8764-2683.
Texto completoTesis sobre el tema "Secure classification"
Neubert, Janek. "Secure WebServer". Thesis, Universitätsbibliothek Chemnitz, 2004. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200400894.
Texto completoJaziri, Rakia. "Modèles de mélanges topologiques pour la classification de données structurées en séquences". Paris 13, 2013. http://scbd-sto.univ-paris13.fr/secure/edgalilee_th_2013_jaziri.pdf.
Texto completoRecent years have seen the development of data mining techniques in various application areas, with the purpose of analyzing sequential, large and complex data. In this work, the problem of clustering, visualization and structuring data is tackled by a three-stage proposal. The first proposal present a generative approach to learn a new probabilistic Self-Organizing Map (PrSOMS) for non independent and non identically distributed data sets. Our model defines a low dimensional manifold allowing friendly visualizations. To yield the topology preserving maps, our model exhibits the SOM like learning behavior with the advantages of probabilistic models. This new paradigm uses HMM (Hidden Markov Models) formalism and introduces relationships between the states. This allows us to take advantage of all the known classical views associated to topographic map. The second proposal concerns a hierarchical extension of the approach PrSOMS. This approach deals the complex aspect of the data in the classification process. We find that the resulting model ”H-PrSOMS” provides a good interpretability of classes built. The third proposal concerns an alternative approach statistical topological MGTM-TT, which is based on the same paradigm than HMM. It is a generative topographic modeling observation density mixtures, which is similar to a hierarchical extension of time GTM model. These proposals have then been applied to test data and real data from the INA (National Audiovisual Institute). This work is to provide a first step, a finer classification of audiovisual broadcast segments. In a second step, we sought to define a typology of the chaining of segments (multiple scattering of the same program, one of two inter-program) to provide statistically the characteristics of broadcast segments. The overall framework provides a tool for the classification and structuring of audiovisual programs
Zabel, Martin, Thomas B. Preußer, Peter Reichel y Rainer G. Spallek. "SHAP-Secure Hardware Agent Platform". Universitätsbibliothek Chemnitz, 2007. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701011.
Texto completoBathe, Shivraj Gajanan. "Secure Communication in a Multi-OS-Environment". Master's thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-196760.
Texto completoPfennig, Stefan y Elke Franz. "Comparison of Different Secure Network Coding Paradigms Concerning Transmission Efficiency". Technische Universität Dresden, 2013. https://tud.qucosa.de/id/qucosa%3A28134.
Texto completoFranz, Elke, Stefan Pfennig y André Fischer. "Communication Overhead of Network Coding Schemes Secure against Pollution Attacks". Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-89807.
Texto completoSleem, Lama. "Design and implementation of lightweight and secure cryptographic algorithms for embedded devices". Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCD018.
Texto completoLiving in an era where new devices are astonishing considering their high capabilities, new visions and terms have emerged. Moving to smart phones, Wireless Sensor Networks, high-resolution cameras, pads and much more, has mandated the need to rethink the technological strategy that is used today. Starting from social media, where apparently everything is being exposed, moving to highly powerful surveillance cameras, in addition to real time health monitoring, it can be seen that a high amount of data is being stored in the Cloud and servers. This introduced a great challenge for their storage and transmission especially in the limited resourced platforms that are characterized by: (a) limited computing capabilities, (b) limited energy and source of power and (c) open infrastructures that transmit data over wireless unreliable networks. One of the extensively studied platforms is the Vehicular Ad-hoc Networks which tends to have many limitations concerning the security field. In this dissertation, we focus on improving the security of transmitted multimedia contents in different limited platforms, while preserving a high security level. Limitations of these platforms are taken into consideration while enhancing the execution time of the secure cipher. Additionally, if the proposed cipher is to be used for images, the intrinsic voluminous and complex nature of the managed images is also taken into account. In the first part, we surveyed one of the limited platforms that is interesting for many researchers, which is the Vehicular Ad-hoc Networks. In order to pave the way for researchers to find new efficient security solutions, it is important to have one reference that can sum most of the recent works. It almost investigates every aspect in this field shedding the light over different aspects this platform possesses. Then, in order to propose any new security solution and validate its robustness and the level of randomness of the ciphered image, a simple and efficient test is proposed. This test proposes using the randomness tools, TestU01 and Practrand, in order to assure a high level of randomness. After running these tests on well known ciphers, some flaws were exposed. Proceeding to the next part, a novel proposal for enhancing the well-known ultra lightweight cipher scheme, Speck, is proposed. The main contribution of this work is to obtain a better version compared to Speck. In this proposal, 26 rounds in Speck were reduced to 7 rounds in Speck-R while enhancing the execution time by at least 50%. First, we validate that Speck-R meets the randomness tests that are previously proposed. Additionally, a dynamic substitution layer adds more security against key related attacks and highly fortifies the cipher. Speck-R was implemented on different limited arduino chips and in all cases, Speck-R was ahead of Speck. Then, in order to prove that this cipher can be used for securing images, especially in VANETS/IoV, where images can be extensively re/transmitted, several tests were exerted and results showed that Speck-R indeed possesses the high level of security desired in any trusted cipher. Extensive experiments validate our proposal from both security and performance point of views and demonstrate the robustness of the proposed scheme against the most-known types of attacks
Pfennig, Stefan y Elke Franz. "Secure Network Coding: Dependency of Efficiency on Network Topology". Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-128456.
Texto completoHo, Zuleita K. M. y Eduard Jorswieck. "Secure degrees of freedom on widely linear instantaneous relay-assisted interference channel". Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-128420.
Texto completoRiedel, Ursula, Frank Richter, Uwe Huebner, Jan Wunderlich, Holger Trapp, Matthias Clauss, Karsten Baensch et al. "Mitteilungen des URZ 1/2/1996". Universitätsbibliothek Chemnitz, 1996. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-199600134.
Texto completoLibros sobre el tema "Secure classification"
Documentos clasificados de la policía secreta de Carías (1937-1944). Tegucigalpa: Instituto Hondureño de Antropología e Historia, 2009.
Buscar texto completoBen-Israel, Isaac. Philosophie du renseignement: Logique et morale de l'espionnage. Paris: Éditions de l'éclat, 2004.
Buscar texto completoHarcourt, Edward, ed. Attachment and Character. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192898128.001.0001.
Texto completoDe Baets, Antoon. Censorship and History since 1945. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199225996.003.0004.
Texto completoCapítulos de libros sobre el tema "Secure classification"
Bergström, Erik y Rose-Mharie Åhlfeldt. "Information Classification Issues". En Secure IT Systems, 27–41. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11599-3_2.
Texto completoAktas, Kursat y Sevil Sen. "UpDroid: Updated Android Malware and Its Familial Classification". En Secure IT Systems, 352–68. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03638-6_22.
Texto completoAlishahi, Mina, Daan Gast y Sam Vermeiren. "Local Differential Privacy for Private Construction of Classification Algorithms". En Secure IT Systems, 58–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-22295-5_4.
Texto completoMalik, Hafiz, Farhan Baqai, Ashfaq Khokhar y Rashid Ansari. "Secure Data-Hiding in Multimedia Using NMF". En Multimedia Content Representation, Classification and Security, 265–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11848035_36.
Texto completoSakib, Sadman, Mostafa M. Fouda y Zubair Md Fadlullah. "Harnessing Artificial Intelligence for Secure ECG Analytics at the Edge for Cardiac Arrhythmia Classification". En Secure Edge Computing, 137–53. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003028635-11.
Texto completoEl Bouny, Lahcen, Mohammed Khalil y Abdellah Adib. "ECG Beat Classification Based on Stationary Wavelet Transform". En Mobile, Secure, and Programmable Networking, 110–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22885-9_11.
Texto completoGabber, E., M. Jakobsson, Y. Matias y A. Mayer. "Curbing junk e-mail via secure classification". En Financial Cryptography, 198–213. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0055484.
Texto completoWang, Fen, Xiaoxuan Li, Xiaotao Huang y Ling Kang. "Improved Document Feature Selection with Categorical Parameter for Text Classification". En Mobile, Secure, and Programmable Networking, 86–98. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50463-6_8.
Texto completoReddy, B. Praeep Kumar y Ayantika Chatterjee. "Encrypted Classification Using Secure K-Nearest Neighbour Computation". En Security, Privacy, and Applied Cryptography Engineering, 176–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35869-3_13.
Texto completoRiyad, Mouad, Mohammed Khalil y Abdellah Adib. "Cross-Subject EEG Signal Classification with Deep Neural Networks Applied to Motor Imagery". En Mobile, Secure, and Programmable Networking, 124–39. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22885-9_12.
Texto completoActas de conferencias sobre el tema "Secure classification"
Gupta, Anand, Manik Singhal, Akash Gangil y Abhishek Mishra. "SDC: Secure deletion classification". En 2011 International Conference on Recent Trends in Information Technology (ICRTIT). IEEE, 2011. http://dx.doi.org/10.1109/icrtit.2011.5972299.
Texto completoBerian, Alex, Kory Staab, Gregory Ditzler, Tamal Bose y Ravi Tandon. "Adversarial Filters for Secure Modulation Classification". En 2021 55th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2021. http://dx.doi.org/10.1109/ieeeconf53345.2021.9723329.
Texto completoFatayer, Tamer S. y Mohammed N. Azara. "IoT Secure Communication using ANN Classification Algorithms". En 2019 International Conference on Promising Electronic Technologies (ICPET). IEEE, 2019. http://dx.doi.org/10.1109/icpet.2019.00033.
Texto completoMaru, Siddharth y Timothy X. Brown. "Packet classification in co-mingled traffic streams". En 2009 5th IEEE Workshop on Secure Network Protocols (NPSec). IEEE, 2009. http://dx.doi.org/10.1109/npsec.2009.5342251.
Texto completoLee, Shan-Hsin, Shen-Chieh Lan, Hsiu-Chuan Huang, Chia-Wei Hsu, Yung-Shiu Chen y Shiuhpyng Shieh. "EC-Model: An Evolvable Malware Classification Model". En 2021 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2021. http://dx.doi.org/10.1109/dsc49826.2021.9346248.
Texto completoVaidya, Jaideep y Bhakti Tulpule. "Enabling Better Medical Image Classification Through Secure Collaboration". En 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4380054.
Texto completoYang, Ziqi. "Fidelity: Towards Measuring the Trustworthiness of Neural Network Classification". En 2019 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2019. http://dx.doi.org/10.1109/dsc47296.2019.8937572.
Texto completoPeixoto, Catarina, Hugo Peixoto, José Machado, António Abelha y Manuel F. Santos. "Iron Value Classification in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis using Data Mining". En Special Session on Healthy and Secure People. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006820802850290.
Texto completoSharma, Seema y Deepti Mehrotra. "Comparative Analysis of Multi-label Classification Algorithms". En 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). IEEE, 2018. http://dx.doi.org/10.1109/icsccc.2018.8703285.
Texto completoArora, Mamta, Sanjeev Dhawan y Kulvinder Singh. "Deep Neural Network for Transformation Zone Classification". En 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). IEEE, 2018. http://dx.doi.org/10.1109/icsccc.2018.8703327.
Texto completoInformes sobre el tema "Secure classification"
Edwards, Mervyn, Matthias Seidl y Alix Edwards. GB LSAV Approval Scheme: Non-ADS requirements D7.1. TRL, junio de 2022. http://dx.doi.org/10.58446/dxiy5599.
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