Literatura académica sobre el tema "Intrusion"
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Artículos de revistas sobre el tema "Intrusion"
Sappin, A. A., M. G. Houlé, D. Corrigan, M. P. Bédard, N. Rayner, N. Wodicka y C. Brind’Amour-Côté. "Petrography, chemical composition, and age constraints of mafic intrusions from the Mesoproterozoic Soisson Intrusive Suite in the southeastern Churchill Province (Canada)". Canadian Journal of Earth Sciences 59, n.º 3 (marzo de 2022): 180–204. http://dx.doi.org/10.1139/cjes-2021-0059.
Texto completoSpenceley, Anna y Bill Jerrom. "Intrusive Traumatic Childhood Memories in Depression: A Comparison Between Depressed, Recovered and Never Depressed Women". Behavioural and Cognitive Psychotherapy 25, n.º 4 (octubre de 1997): 309–18. http://dx.doi.org/10.1017/s1352465800018713.
Texto completoWilson, Penelope I. R., Ken J. W. McCaffrey y Robert E. Holdsworth. "Magma-driven accommodation structures formed during sill emplacement at shallow crustal depths: The Maiden Creek sill, Henry Mountains, Utah". Geosphere 15, n.º 4 (24 de junio de 2019): 1368–92. http://dx.doi.org/10.1130/ges02067.1.
Texto completoRombold, F., K. Wingenfeld, B. Renneberg, J. Hellmann-Regen, C. Otte y S. Roepke. "Influence of the noradrenergic system on the formation of intrusive memories in women: an experimental approach with a trauma film paradigm". Psychological Medicine 46, n.º 12 (23 de junio de 2016): 2523–34. http://dx.doi.org/10.1017/s0033291716001379.
Texto completoROBINS, BRIAN. "The mode of emplacement of the Honningsvåg Intrusive Suite, Magerøya, northern Norway". Geological Magazine 135, n.º 2 (marzo de 1998): 231–44. http://dx.doi.org/10.1017/s0016756898008395.
Texto completoHUGHES, HANNAH S. R., KATHRYN M. GOODENOUGH, ABIGAIL S. WALTERS, MICHAEL MCCORMAC, A. GUS GUNN y ALICJA LACINSKA. "The structure and petrology of the Cnoc nan Cuilean Intrusion, Loch Loyal Syenite Complex, NW Scotland". Geological Magazine 150, n.º 5 (22 de febrero de 2013): 783–800. http://dx.doi.org/10.1017/s0016756812000957.
Texto completoCanhimbue, Ludmila y Irina Talovina. "Geochemical Distribution of Platinum Metals, Gold and Silver in Intrusive Rocks of the Norilsk Region". Minerals 13, n.º 6 (24 de mayo de 2023): 719. http://dx.doi.org/10.3390/min13060719.
Texto completoHorsman, Eric, Sven Morgan, Michel de Saint-Blanquat, Guillaume Habert, Andrew Nugent, Robert A. Hunter y Basil Tikoff. "Emplacement and assembly of shallow intrusions from multiple magma pulses, Henry Mountains, Utah". Earth and Environmental Science Transactions of the Royal Society of Edinburgh 100, n.º 1-2 (marzo de 2009): 117–32. http://dx.doi.org/10.1017/s1755691009016089.
Texto completoPriyavengatesh, A. "A Predictive Model Using Deep Learning Neural Network for Efficient Intrusion Detection". International Journal for Research in Applied Science and Engineering Technology 11, n.º 10 (31 de octubre de 2023): 577–85. http://dx.doi.org/10.22214/ijraset.2023.56020.
Texto completoSolomon, Irin Anna, Aman Jatain y Shalini Bhaskar Bajaj. "Intrusion Detection System Using Deep Learning". Asian Journal of Computer Science and Technology 8, n.º 2 (5 de mayo de 2019): 105–10. http://dx.doi.org/10.51983/ajcst-2019.8.2.2132.
Texto completoTesis sobre el tema "Intrusion"
Olsson, Fredrik. "Intrusion Management". Thesis, Växjö University, School of Mathematics and Systems Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-794.
Texto completoInformation security is tasked with protecting the confidentiality, integrity, and availability of an organizations information resource. A key aspect in protecting these resources is developing an
understanding of the threats, vulnerabilities, and exposures that they face by using Risk Management.
The objective of Risk Management is to identify, quantify and manage information security risks to achieve organizations objectives through a number of tasks utilizing key Risk Management techniques.
Risk Management is a process that ensures that the impact of threats exploiting vulnerabilities is within acceptable limits and at an acceptable cost.
With the increased complexity of modern dynamic networks, traditional defence mechanisms are failing and as a result cyber crime is on the rise [FBI03]. This puts organizations and corporations at risk as the defences are ill-fitted and weak [KBM04].
No information system can be absolutely secure, especially large and complex systems. Embedded security works for isolated, dedicated systems with few users but does not offer cost effective security, and even worse does not always handle security based on a real threat (this is manly due to it inherent inflexibility). A military strategy within the field of information operations suggests a method of information superiority bases on the OODA-loop. This theses propose a method of information security protection based on a combination of risk management techniques and information operation (foremost the OODA-loop). This is in order to ensure a cost effective and a viable future for information security in large
and complex systems, where the war at least at present time is lost to the “black hats”, a term often used to describe a menaced hacker.
Jim, Nilsson. "Fracture characterization in magmatic rock, a case study of the Sosa-dyke (Neuquén Basin, Argentina)". Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-411548.
Texto completoI hela världen finns det många exempel där stelnade magmatiska intrusioner påverka ett områdes vatten och energiförsörjning, på grund av att intrusioner kan agera som ledare och reservoarer men också som barriärer för vätskor och gaser in marken. Den avgörande faktorn mellan ledare och barriärer i en intrusion är dess spricknätverk. Därför är det viktigt att kartlägga och karakterisera en intrusions spricknätverk och därmed också få en uppfattning om dess permeabilitet. Magmatiska intrusioner är förutom genom borrhål ofta svåråtkomliga, det finns därför väldigt lite information om hur de påverkar akviferer och reservoarer i marken. Det är därför viktigt att öka kunskapen om magmatiska intrusioner genom att undersöka intrusionerna som är tillgängliga vid markytan. I denna studie har bilder från en fallstudie om Sosa Intrusionen använts för att kartera och karakterisera sprickor i Sosa intrusionen. Det är en vertikal magmatisk intrusion som är synlig på markytan, och en del av Chachahuén vulkan komplexet i sydvästra Argentina. Bilderna som användes är tagna med en UAV( unmanned aerial vehicle), och för att analysera bilderna, kartera sprickorna och producera resultaten, användes programmen Agisoft Metashape, MOVE™ och MATLAB med FracPaQ verktyget. Intrusionen har två distinkta sprickgrupper, en som är vinkelrät mot intrusionens kanter och en som går parallellt med kanterna. Konnektivitet mellan sprickorna är låg och eftersom permeabiliteten påverkas av konnektiviteten är den också låg. Sprickgruppen som är vinkelrätt mot intrusionskanten är så kallade kylningssprickor och bildas nät magman i intrusionen svalnar. Det leder till att magman kontraherar och spricker, och bildar sprickor som går inåt mot stelningsgränsen och därmed vinkelrätt mot intrusionskanten. Sprickgruppen som går parallellt med intrusionen bildas av att mineral i magmaströmmen påverkas av friktion från intrusionskanterna. Det gör att mineralen lägger sig och sträcks ut i samma riktning som magmaflödet, vilket när magman stelnar bildar svaghetszoner som sprickor kan fortplanta sig i. Dessa sprickgrupper har låg konnektivitet vilket gör att slutsatsen blir att det karterade området av Sosa intrusionen har låg permeabilitet.
Ferreira, Eduardo Alves. "Detecção autônoma de intrusões utilizando aprendizado de máquina". Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-28072011-160306/.
Texto completoThe use of computers to automatically perform operational tasks is commonplace, thanks to the information technology evolution. The maintenance of computer systems, on the other hand, is commonly performed manually, resulting in high costs, low productivity and low quality of service. The Autonomous Computing initiative aims to approach this limitation, through selfmanagement of computer systems. In order to assemble a fully autonomous system, an intrusion detection application is needed to monitor the behavior and data flows on applications. Considering this context, an autonomous Web intrusion detection system is proposed, based on machine-learning techniques with near-linear computational complexity. This system is based on clustering and novelty detection techniques, characterizing an application behavior, to later pinpoint anomalies in live applications. By conducting experiments, we observed that this new approach is capable of detecting anomalies with less dependency on specific contexts than previous solutions
Stefanova, Zheni Svetoslavova. "Machine Learning Methods for Network Intrusion Detection and Intrusion Prevention Systems". Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7367.
Texto completoChatprechakul, Nattapron. "Improving performance of distributed network intrusion intrusion detection systems using mobile agents". Thesis, Cranfield University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.423508.
Texto completoChevalier, Ronny. "Detecting and Surviving Intrusions : Exploring New Host-Based Intrusion Detection, Recovery, and Response Approaches". Thesis, CentraleSupélec, 2019. http://www.theses.fr/2019CSUP0003.
Texto completoComputing platforms, such as embedded systems or laptops, are built with layers of preventive security mechanisms to reduce the likelihood of attackers successfully compromising them. Nevertheless, given time and despite decades of improvements in preventive security, intrusions still happen. Therefore, systems should expect intrusions to occur, thus they should be built to detect and to survive them.Commodity Operating Systems (OSs) are deployed with intrusion detection solutions, but their ability to survive them is limited. State-of-the-art approaches from industry or academia either involve manual procedures, loss of availability, coarse-grained responses, or non-negligible performance overhead. Moreover, low-level components, such as the BIOS, are increasingly targeted by sophisticated attackers to implant stealthy and resilient malware. State-of-the-art solutions, however, mainly focus on boot time integrity, leaving the runtime part of the BIOS—known as the System Management Mode (SMM)—a prime target.This dissertation shows that we can build platforms that detect intrusions at the BIOS level and survive intrusions at the OS level. First, by demonstrating that intrusion survivability is a viable approach for commodity OSs. We develop a new approach that address various limitations from the literature, and we evaluate its security and performance. Second, by developing a hardware-based approach that detects attacks at the BIOS level where we demonstrate its feasibility with multiple detection methods
Vigo, John Louis Jr. "Wireless Intrusion Detection Sytem". ScholarWorks@UNO, 2004. http://scholarworks.uno.edu/td/203.
Texto completoWeigert, Stefan. "Community-Based Intrusion Detection". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-217677.
Texto completoJacoby, Grant Arthur. "Battery-Based Intrusion Detection". Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/27092.
Texto completoPh. D.
Jacoby, Grant A. "Battery-based intrusion detection /". This resource online, 2005. http://scholar.lib.vt.edu/theses/available/etd-04212005-120840.
Texto completoLibros sobre el tema "Intrusion"
Intrusion. London: Orbit, 2012.
Buscar texto completoIntrusion. Paris: Pocket, 2012.
Buscar texto completoIntrusion. Bloomington, Indiana]: Xlibris, 2014.
Buscar texto completoAlien intrusion. Green Forest, AR: Master Books, 2004.
Buscar texto completoSengupta, Nandita y Jaya Sil. Intrusion Detection. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2716-6.
Texto completoIntrusion detection. Indianapolis, IN: Macmillan Technical Publishing, 2000.
Buscar texto completoLaw Reform Commission of Canada. Criminal intrusion. Ottawa, Canada: The Commission, 1986.
Buscar texto completoThe intrusion. [United States]: Innovo Publishing, 2010.
Buscar texto completoOlgin, Howard. Remote intrusion. New York: Dell Book, 1996.
Buscar texto completoCriminal intrusion. Ottawa: Law Reform Commission of Canada, 1986.
Buscar texto completoCapítulos de libros sobre el tema "Intrusion"
Weik, Martin H. "intrusion". En Computer Science and Communications Dictionary, 833. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_9555.
Texto completoSengupta, Nandita y Jaya Sil. "Introduction". En Intrusion Detection, 1–25. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2716-6_1.
Texto completoSengupta, Nandita y Jaya Sil. "Discretization". En Intrusion Detection, 27–46. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2716-6_2.
Texto completoSengupta, Nandita y Jaya Sil. "Data Reduction". En Intrusion Detection, 47–82. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2716-6_3.
Texto completoSengupta, Nandita y Jaya Sil. "Q-Learning Classifier". En Intrusion Detection, 83–111. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2716-6_4.
Texto completoSengupta, Nandita y Jaya Sil. "Conclusions and Future Research". En Intrusion Detection, 113–18. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2716-6_5.
Texto completoYi, Myung-Kyu y Chong-Sun Hwang. "Intrusion-Tolerant Intrusion Detection System". En Intelligence and Security Informatics, 476–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25952-7_38.
Texto completoBace, Rebecca Gurley. "Intrusion Detection and Intrusion Prevention Devices". En Computer Security Handbook, 27.1–27.18. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781118851678.ch27.
Texto completoPerez, André. "Intrusion Detection". En Network Security, 237–51. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119043942.ch10.
Texto completoHaberlandt, Karl. "Intrusion Errors". En Encyclopedia of Clinical Neuropsychology, 1353–54. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_1131.
Texto completoActas de conferencias sobre el tema "Intrusion"
Järvinen, V. y T. Halkoaho. "Formation of poikilitic chromite in the basal dunite series of the 2.44 Ga Näränkävaara layered intrusion". En Project KO5125 ARLIN Arctic Layered Intrusions as a Source of Critical Metals for Green Economy European Neighbourhood Instrument Cross-Border Cooperation Programme Kolarctic 2014-2020. GI KSC RAS, 2022. http://dx.doi.org/10.31241/arlin.2022.004.
Texto completoBulegenov, Kanat, Sayat Rais y Daulet Muratkhanov. "GEOLOGY OF PERMIAN GRANITES OF THE KARATAU-NARYN ZONE AND THEIR PROSPECTIVE FOR RARE METALS (SOUTH KAZAKHSTAN)". En 23rd SGEM International Multidisciplinary Scientific GeoConference 2023. STEF92 Technology, 2023. http://dx.doi.org/10.5593/sgem2023/1.1/s01.07.
Texto completoSilva Neto, Manuel Gonçalves da y Danielo G. Gomes. "Network Intrusion Detection Systems Design: A Machine Learning Approach". En XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbrc.2019.7413.
Texto completoPrasad, Romesh y Young Moon. "Adaptive Intrusion Detection System for Cyber-Manufacturing System". En ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-70017.
Texto completoS. P, Sujini, AnbuShamini G. N y Prija J. S. "Deep Intrusion Detection for DOS and DDOS Attacks Using LSTM and Deep Autoencoder Neural Network". En The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/qkfn6548/ngcesi23p93.
Texto completoElaeraj, Ouafae y Cherkaoui Leghris. "The Evolution of Vector Machine Support in the Field of Intrusion Detection Systems". En 2nd International Conference on Machine Learning Techniques and Data Science (MLDS 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111817.
Texto completoLowe, Ryan J. "A Laboratory Study of the Velocity Structure in an Intrusive Gravity Current". En ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-2088.
Texto completoCastanhel, Gabriel Ruschel, Tiago Heinrich, Fabrício Ceschin y Carlos A. Maziero. "Sliding Window: The Impact of Trace Size in Anomaly Detection System for Containers Through Machine Learning". En XVIII Escola Regional de Redes de Computadores. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/errc.2020.15203.
Texto completoGuimaraes, Mario y Meg Murray. "Overview of intrusion detection and intrusion prevention". En the 5th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1456625.1456638.
Texto completoAnand, Vijay. "Intrusion Detection". En the 2014 ACM SIGUCCS Annual Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2661172.2661186.
Texto completoInformes sobre el tema "Intrusion"
Pilny, Julia. Investigating Network Intrusion. Fort Belvoir, VA: Defense Technical Information Center, enero de 2003. http://dx.doi.org/10.21236/ada412544.
Texto completoTomko, Albert A., Christian J. Rieser, Louis H. Buell, David R. Zaret y William M. Turner. Wireless Intrusion Detection. Fort Belvoir, VA: Defense Technical Information Center, marzo de 2007. http://dx.doi.org/10.21236/ada466332.
Texto completoBace, Rebecca y Peter Mell. Intrusion detection systems. Gaithersburg, MD: National Institute of Standards and Technology, 2001. http://dx.doi.org/10.6028/nist.sp.800-31.
Texto completoSchnackenberg, Dan, Harley Holliday, Travis Reid, Kelly Bunn y Dan Sterne. Automatic Response to Intrusion. Fort Belvoir, VA: Defense Technical Information Center, octubre de 2002. http://dx.doi.org/10.21236/ada408394.
Texto completoGiffin, Jonathan T., David Dagon, Somesh Jha, Wenke Lee y Barton P. Miller. Environment-Sensitive Intrusion Detection. Fort Belvoir, VA: Defense Technical Information Center, enero de 2006. http://dx.doi.org/10.21236/ada448428.
Texto completoRodriguez, J. R., J. C. Matter y B. Dry. Interior intrusion detection systems. Office of Scientific and Technical Information (OSTI), octubre de 1991. http://dx.doi.org/10.2172/5977693.
Texto completoCowles, Robert D. Intrusion Detection and Physics. Office of Scientific and Technical Information (OSTI), febrero de 1999. http://dx.doi.org/10.2172/10009.
Texto completoFirth, Robert, Gary Ford, Barbara Fraser, John Kochmar y Suresh Konda. Detecting Signs of Intrusion. Fort Belvoir, VA: Defense Technical Information Center, agosto de 1997. http://dx.doi.org/10.21236/ada329629.
Texto completoWu, Thomas, Michael Malkin y Dan Boneh. Building Intrusion Tolerant Applications. Fort Belvoir, VA: Defense Technical Information Center, enero de 2001. http://dx.doi.org/10.21236/ada387165.
Texto completoHinkebein, T. E., S. J. Bauer, B. L. Ehgartner, J. K. Linn, J. T. Neal, J. L. Todd, P. S. Kuhlman, C. T. Gniady y H. N. Giles. Gas intrusion into SPR caverns. Office of Scientific and Technical Information (OSTI), diciembre de 1995. http://dx.doi.org/10.2172/206492.
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