Academic literature on the topic 'Secure classification'
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Journal articles on the topic "Secure classification"
Pearson, Jane L., Deborah A. Cohn, Philip A. Cowan, and Carolyn Pape Cowan. "Earned- and continuous-security in adult attachment: Relation to depressive symptomatology and parenting style." Development and Psychopathology 6, no. 2 (1994): 359–73. http://dx.doi.org/10.1017/s0954579400004636.
Full textHareesha, K. S., and M. Sumana. "Secure Two Party Privacy Preserving Classification Using Encryption." International Journal of Information and Electronics Engineering 6, no. 2 (2016): 67–71. http://dx.doi.org/10.18178/ijiee.2016.6.2.597.
Full textBaars, Thijs, and Marco Spruit. "Designing a Secure Cloud Architecture." International Journal of Information Security and Privacy 6, no. 1 (January 2012): 14–32. http://dx.doi.org/10.4018/jisp.2012010102.
Full textT., Tamanna, and Rajeev Kumar. "Secure Cloud Model using Classification and Cryptography." International Journal of Computer Applications 159, no. 6 (February 15, 2017): 8–13. http://dx.doi.org/10.5120/ijca2017912953.
Full textUsharani, A. V., and Girija Attigeri. "Secure EMR Classification and Deduplication Using MapReduce." IEEE Access 10 (2022): 34404–14. http://dx.doi.org/10.1109/access.2022.3161439.
Full textWiseman, Simon R. "Classification services in the SWORD secure DBMS." Computers & Security 14, no. 4 (January 1995): 307–21. http://dx.doi.org/10.1016/0167-4048(95)00004-r.
Full textSalehi, Mahmood, and Azzedine Boukerche. "Secure opportunistic routing protocols: methods, models, and classification." Wireless Networks 25, no. 2 (September 11, 2017): 559–71. http://dx.doi.org/10.1007/s11276-017-1575-1.
Full text., S. Narayanan. "CLASSIFICATION OF SECURE ENCRYPTED RELATIONALDATA IN CLOUD COMPUTING." International Journal of Research in Engineering and Technology 05, no. 03 (March 25, 2016): 159–66. http://dx.doi.org/10.15623/ijret.2016.0503034.
Full textS L Swapna and V Saravanan. "Jaccard Index Cat Gradient Boosting Classification for Secured Big Data Communication." Applied Science and Engineering Journal for Advanced Research 1, no. 5 (September 30, 2022): 1–14. http://dx.doi.org/10.54741/asejar.1.5.1.
Full textB, Murugeshwari, Jayakumar C, and Sarukesi K. "Secure Multi Party Computation Technique for Classification Rule Sharing." International Journal of Computer Applications 55, no. 7 (October 20, 2012): 1–10. http://dx.doi.org/10.5120/8764-2683.
Full textDissertations / Theses on the topic "Secure classification"
Neubert, Janek. "Secure WebServer." Thesis, Universitätsbibliothek Chemnitz, 2004. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200400894.
Full textJaziri, 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.
Full textRecent 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, and Rainer G. Spallek. "SHAP-Secure Hardware Agent Platform." Universitätsbibliothek Chemnitz, 2007. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701011.
Full textBathe, 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.
Full textPfennig, Stefan, and Elke Franz. "Comparison of Different Secure Network Coding Paradigms Concerning Transmission Efficiency." Technische Universität Dresden, 2013. https://tud.qucosa.de/id/qucosa%3A28134.
Full textFranz, Elke, Stefan Pfennig, and 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.
Full textSleem, Lama. "Design and implementation of lightweight and secure cryptographic algorithms for embedded devices." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCD018.
Full textLiving 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, and 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.
Full textHo, Zuleita K. M., and 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.
Full textRiedel, 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.
Full textBooks on the topic "Secure classification"
Documentos clasificados de la policía secreta de Carías (1937-1944). Tegucigalpa: Instituto Hondureño de Antropología e Historia, 2009.
Find full textBen-Israel, Isaac. Philosophie du renseignement: Logique et morale de l'espionnage. Paris: Éditions de l'éclat, 2004.
Find full textHarcourt, Edward, ed. Attachment and Character. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192898128.001.0001.
Full textDe Baets, Antoon. Censorship and History since 1945. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199225996.003.0004.
Full textBook chapters on the topic "Secure classification"
Bergström, Erik, and Rose-Mharie Åhlfeldt. "Information Classification Issues." In Secure IT Systems, 27–41. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11599-3_2.
Full textAktas, Kursat, and Sevil Sen. "UpDroid: Updated Android Malware and Its Familial Classification." In Secure IT Systems, 352–68. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03638-6_22.
Full textAlishahi, Mina, Daan Gast, and Sam Vermeiren. "Local Differential Privacy for Private Construction of Classification Algorithms." In Secure IT Systems, 58–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-22295-5_4.
Full textMalik, Hafiz, Farhan Baqai, Ashfaq Khokhar, and Rashid Ansari. "Secure Data-Hiding in Multimedia Using NMF." In Multimedia Content Representation, Classification and Security, 265–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11848035_36.
Full textSakib, Sadman, Mostafa M. Fouda, and Zubair Md Fadlullah. "Harnessing Artificial Intelligence for Secure ECG Analytics at the Edge for Cardiac Arrhythmia Classification." In Secure Edge Computing, 137–53. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003028635-11.
Full textEl Bouny, Lahcen, Mohammed Khalil, and Abdellah Adib. "ECG Beat Classification Based on Stationary Wavelet Transform." In Mobile, Secure, and Programmable Networking, 110–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22885-9_11.
Full textGabber, E., M. Jakobsson, Y. Matias, and A. Mayer. "Curbing junk e-mail via secure classification." In Financial Cryptography, 198–213. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0055484.
Full textWang, Fen, Xiaoxuan Li, Xiaotao Huang, and Ling Kang. "Improved Document Feature Selection with Categorical Parameter for Text Classification." In Mobile, Secure, and Programmable Networking, 86–98. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50463-6_8.
Full textReddy, B. Praeep Kumar, and Ayantika Chatterjee. "Encrypted Classification Using Secure K-Nearest Neighbour Computation." In 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.
Full textRiyad, Mouad, Mohammed Khalil, and Abdellah Adib. "Cross-Subject EEG Signal Classification with Deep Neural Networks Applied to Motor Imagery." In Mobile, Secure, and Programmable Networking, 124–39. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22885-9_12.
Full textConference papers on the topic "Secure classification"
Gupta, Anand, Manik Singhal, Akash Gangil, and Abhishek Mishra. "SDC: Secure deletion classification." In 2011 International Conference on Recent Trends in Information Technology (ICRTIT). IEEE, 2011. http://dx.doi.org/10.1109/icrtit.2011.5972299.
Full textBerian, Alex, Kory Staab, Gregory Ditzler, Tamal Bose, and Ravi Tandon. "Adversarial Filters for Secure Modulation Classification." In 2021 55th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2021. http://dx.doi.org/10.1109/ieeeconf53345.2021.9723329.
Full textFatayer, Tamer S., and Mohammed N. Azara. "IoT Secure Communication using ANN Classification Algorithms." In 2019 International Conference on Promising Electronic Technologies (ICPET). IEEE, 2019. http://dx.doi.org/10.1109/icpet.2019.00033.
Full textMaru, Siddharth, and Timothy X. Brown. "Packet classification in co-mingled traffic streams." In 2009 5th IEEE Workshop on Secure Network Protocols (NPSec). IEEE, 2009. http://dx.doi.org/10.1109/npsec.2009.5342251.
Full textLee, Shan-Hsin, Shen-Chieh Lan, Hsiu-Chuan Huang, Chia-Wei Hsu, Yung-Shiu Chen, and Shiuhpyng Shieh. "EC-Model: An Evolvable Malware Classification Model." In 2021 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2021. http://dx.doi.org/10.1109/dsc49826.2021.9346248.
Full textVaidya, Jaideep, and Bhakti Tulpule. "Enabling Better Medical Image Classification Through Secure Collaboration." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4380054.
Full textYang, Ziqi. "Fidelity: Towards Measuring the Trustworthiness of Neural Network Classification." In 2019 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2019. http://dx.doi.org/10.1109/dsc47296.2019.8937572.
Full textPeixoto, Catarina, Hugo Peixoto, José Machado, António Abelha, and Manuel F. Santos. "Iron Value Classification in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis using Data Mining." In Special Session on Healthy and Secure People. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006820802850290.
Full textSharma, Seema, and Deepti Mehrotra. "Comparative Analysis of Multi-label Classification Algorithms." In 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). IEEE, 2018. http://dx.doi.org/10.1109/icsccc.2018.8703285.
Full textArora, Mamta, Sanjeev Dhawan, and Kulvinder Singh. "Deep Neural Network for Transformation Zone Classification." In 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). IEEE, 2018. http://dx.doi.org/10.1109/icsccc.2018.8703327.
Full textReports on the topic "Secure classification"
Edwards, Mervyn, Matthias Seidl, and Alix Edwards. GB LSAV Approval Scheme: Non-ADS requirements D7.1. TRL, June 2022. http://dx.doi.org/10.58446/dxiy5599.
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