Academic literature on the topic 'Intrusive windows'
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Journal articles on the topic "Intrusive windows"
He, Xi, Heng Dong, Wanli Yang, and Jun Hong. "A Novel Denoising Auto-Encoder-Based Approach for Non-Intrusive Residential Load Monitoring." Energies 15, no. 6 (March 21, 2022): 2290. http://dx.doi.org/10.3390/en15062290.
Full textMassoz, Quentin, Jacques Verly, and Marc Van Droogenbroeck. "Multi-Timescale Drowsiness Characterization Based on a Video of a Driver’s Face." Sensors 18, no. 9 (August 25, 2018): 2801. http://dx.doi.org/10.3390/s18092801.
Full textSiqueira Cassiano, Marcella. "China’s Hukou Platform: Windows into the Family." Surveillance & Society 17, no. 1/2 (March 31, 2019): 232–39. http://dx.doi.org/10.24908/ss.v17i1/2.13125.
Full textLiu, Lin, Yuehua Jiang, Xun Zhou, Yun Li, Quanping Zhou, Jingwen Su, Junyuan Jia, Guoqiang Yang, and Yang Jin. "Long-Lasting Boiling-Wells: Geochemical Windows into the Tectonic Activity of the Maodong Fault (China)." Water 14, no. 3 (January 29, 2022): 427. http://dx.doi.org/10.3390/w14030427.
Full textAshton, K. E., J. F. Lewry, L. M. Heaman, R. P. Hartlaub, M. R. Stauffer, and H. T. Tran. "The Pelican Thrust Zone: basal detachment between the Archean Sask Craton and Paleoproterozoic Flin Flon Glennie Complex, western Trans-Hudson Orogen." Canadian Journal of Earth Sciences 42, no. 4 (April 1, 2005): 685–706. http://dx.doi.org/10.1139/e04-035.
Full textZhang, Guoming, Xiaoyu Ji, Yanjie Li, and Wenyuan Xu. "Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid." Sensors 20, no. 13 (June 28, 2020): 3635. http://dx.doi.org/10.3390/s20133635.
Full textShi, Yongtao, Xiaodong Zhao, Fan Zhang, and Yaguang Kong. "Non-Intrusive Load Monitoring Based on Swin-Transformer with Adaptive Scaling Recurrence Plot." Energies 15, no. 20 (October 21, 2022): 7800. http://dx.doi.org/10.3390/en15207800.
Full textMa, Yongfeng, Zhuopeng Xie, Shuyan Chen, Ying Wu, and Fengxiang Qiao. "Real-Time Driving Behavior Identification Based on Multi-Source Data Fusion." International Journal of Environmental Research and Public Health 19, no. 1 (December 29, 2021): 348. http://dx.doi.org/10.3390/ijerph19010348.
Full textSaralegui, Unai, Miguel Antón, Olatz Arbelaitz, and Javier Muguerza. "Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles." Sensors 19, no. 2 (January 16, 2019): 353. http://dx.doi.org/10.3390/s19020353.
Full textCorriveau, Louise, and Otto van Breemen. "Docking of the Central Metasedimentary Belt to Laurentia in geon 12: evidence from the 1.17-1.16 Ga Chevreuil intrusive suite and host gneisses, Quebec." Canadian Journal of Earth Sciences 37, no. 2-3 (April 2, 2000): 253–69. http://dx.doi.org/10.1139/e00-004.
Full textDissertations / Theses on the topic "Intrusive windows"
Korba, Jonathan (Jonathan James) 1977. "Windows NT attacks for the evaluation of intrusion detection systems." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86454.
Full textIncludes bibliographical references (leaves 99-101).
by Jonathan Korba.
S.B.and M.Eng.
Kremer, H. Steven. "Real-time intrusion detection for Windows NT based on Navy IT-21 audit policy." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA378151.
Full text"September 1999". Thesis advisors(s): Neil C. Rowe, Ronald Broersma. Includes bibliographical references (p. 49). Also available online.
Telling, Henric, and Anders Gunnarsson. "DNSSEC en säkerhetsförbättring av DNS : en studie om Svenska kommuners syn på DNSSEC." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-12746.
Full textThe purpose of this paper is to investigate why few Swedish municipalities have chosen to install DNSSEC on their domains. DNS is one of the most important protocols on the Internet and used to link IP-addresses to understandable addresses for users. DNS was created without thinking about security, to make DNS more secure a security extension was developed to DNS, named DNSSEC.We have used literature review, experiments and interviews to create a deeper knowledge and understanding about DNS and DNSSEC, how it works and why few municipalities have chosen to install DNSSEC.In the literature we read about several vulnerabilities in DNS and it can easily be exposed to attacks such as cache poisoning and MITM. We tested these vulnerabilities and confirmed them. After installation of DNSSEC we could not expose our implemented DNS anymore in our test environment.During the interviews, we concluded that the most common reason why municipalities do not choose to install DNSSEC is ignorance of an installation and they think that their current DNS works well and it does not become a priority. The municipalities that have installed DNSSEC are satisfied with its installation and only one municipality has experienced difficulties during the implementation.In order for us to continue developing the Internet a control of security is a necessity and DNSSEC is a good example. Local authorities should lead by good example and be among the first to implement DNSSEC, so users of their websites can be assured that the information on their pages is accurate.
Heide, Richter, Riedel, Schier, Kratzert, and Ziegler. "Mitteilungen des URZ 2/2004." Universitätsbibliothek Chemnitz, 2004. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200400568.
Full textLiang, Chih-Hsiang, and 梁志翔. "Building an Attack Scenario Database with Causal Relationship of Intrusive Behaviors in Windows System and DDoS Attack." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/41648834660339446472.
Full text國立成功大學
電腦與通信工程研究所
96
As the coming of information era, Internet becomes popular and starts to offer more and more services. But the account for the security incidents, such as intrusions, viruses, and worms also increases simultaneously. Although many network security devices are used in most enterprises and departments of government for protecting assets, there still exist some problems: First, more network security devices make it difficult to manage and analyze alerts; Second, most duplicate and false positive alerts increase system computing load, storage size and correlation time; Third, we do not have any method to observe the relationship among alerts, system managers cannot identify whether monitored hosts are under attacks and which kinds of attacks they are suffered from; Fourth, no warning system is developed to tell system managers the most possible follow-up attacks that will be launched in the directory future, that’s always leading to very high loss. Take these problems into account, our lab stars to research Security Operation Center (SOC) and has developed several related technologies. Our proposed prototype SOC [8] has 5 main units: 1.) Alert Generator Unit: including 2 sensors and IDMEF format transformation method; 2.) SOC Database: used to store normalized alerts; 3.) Core Procedure Unit: with the functionalities of alert classification, verification, integration and correlation; 4.) System Operation Unit: announcing incident tickets to administrator when monitored hosts are under attacks; 5.) Event Reaction: an user interface to represent incident lists, security statistics and attack graphs. In order to predict all possible trajectories the intruders will go through, our lab also established Attack Scenario Database [5,10], and developed an algorithm, ASGCR, to generation attack scenarios. The enhanced SOC has 4 main units: 1.) Attack Scenario Database: used to store Pre/Post conditions and attack patterns; 2.) Host Detection Unit: adding the account for the sensors to 7; 3.) Alert Correlation Unit: correlating low-level alerts into high-level attack scenarios; 4.) Attack Status and Prediction Unit: generating attack status graphs, including current state and predictive attack scenarios. However, our proposed SOC still has some shortcomings to improve, such as more sensors can be expanded to enhance the ability to detect various attack types, more duplicate alerts and false positive alerts reported from sensors, more attack types can be expanded into attack scenario database, more false positive predictive attack scenarios generated by our developed prediction approach, lacking for a risk evaluation mechanism to help system managers effectively find out the most critical attack scenario,…etc. In order to prove these problems, we expand 4 units in this paper: 1.) Alert Generator Unit: we add 7 types, 13 sensors, to enhance the detection ability; 2.) Alert (attack scenario) Reduction Unit: discarding duplicate alerts or false positive alerts (attack scenarios) to reduce the computing load, system storage and correlation time; 3.) Attack Scenario Database: expanding two attack types “Windows Intrusive” and “DDoS Attack”; 4.) Risk Evaluation and Ranking Unit: provide a list of the most n critical attack scenarios to help system managers understand the most possible follow-up attacks and rapidly make right decision to reduce loss.
Lo, Sheng-Feng, and 羅晟峯. "Trojan virus detection on Windows 7 by using host-based intrusion detection." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/20818620553254179697.
Full text健行科技大學
資訊工程系碩士班
102
Windows 7 is one of the most popular operating system, because of its popularity often become the target of attacks, and Trojan virus is one of them. Trojans hope to be able to hide itself and boot automatically execute reached keyloggers to steal data, control, and so behavior. Therefore, our study presents a method to detect viruses, boot registry keys will be automatically executed and the program has a function to remove registry keys are classified into two rules. These two rules will be to determine whether the main basis for the Trojans, and use host-based intrusion detection system for detection is based on these two rules will be changed in the registry keys to record and count the results. Finally, the statistical results of normal programs and Trojan viruses to compare and analyze changes to registry key behavior. Statistics from the experimental results that the majority of the Trojan virus will tamper with the boot registry keys automatically. In this study, 94% of detection rate, and the false alarm rate of 6%.
Pollock, Meagen. "Geochemistry of Dikes and Lavas from Tectonic Windows." Diss., 2007. http://hdl.handle.net/10161/388.
Full textDissertation
Lin, Shih-Chieh, and 林世杰. "A Study of Intrusion Detection System Based on Anomaly Detection in Windows Environment." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/50284166653456932652.
Full text國立雲林科技大學
資訊管理系碩士班
91
The network intrusion events increased year by year. With the various threaten attack technique, it’s the most concerned issue for MIS personnel to protect the information on the internet. Most researcher developed their IDS based on the Linux platform regardless of the Windows platform. In this study, we proposed an integrated intrusion detection system which is running on the Windows platform, combined with network-based and host-based techniques. We adopted self-organizing map(SOM) method to extract the features of normal behaviors in order to distingwish with the abnormal behavior like intrusion or attack. Unlike other techniques, our method need not to be updated regularly. Therefore, our proposed system could insure the safety against intrusion and maintain easily.
Books on the topic "Intrusive windows"
University of Bath. Centre for Window & Cladding Technology. Windows with enhanced resistance to intrusion. Claverton: Centre for Window and Cladding Technology, 1994.
Find full textAlassouli, Hidaia Mahmood. Overview of Some Windows and Linux Intrusion Detection Tools. Independently Published, 2018.
Find full textReal-Time Intrusion Detection for Windows NT Based on Navy IT-21 Audit Policy. Storming Media, 1999.
Find full textBook chapters on the topic "Intrusive windows"
Battistoni, Roberto, Emanuele Gabrielli, and Luigi V. Mancini. "A Host Intrusion Prevention System for Windows Operating Systems." In Computer Security – ESORICS 2004, 352–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30108-0_22.
Full textVerma, Vinita, Sunil K. Muttoo, and V. B. Singh. "Detecting Stegomalware: Malicious Image Steganography and Its Intrusion in Windows." In Security, Privacy and Data Analytics, 103–16. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9089-1_9.
Full textViswanath, P., M. Narasimha Murty, and Satish Kambala. "An Efficient Parzen-Window Based Network Intrusion Detector Using a Pattern Synthesis Technique." In Lecture Notes in Computer Science, 799–804. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11590316_129.
Full textWilliams, Michael T., and Jasha Kistler. "Utilizing a Modified AAMA 501.1 Dynamic Wind Generation to Simulate Wind-Driven Rain in Windows, Curtain Walls, Architectural Metal Walls, Masonry, EIFS, and Concrete Facades." In Building Walls Subject to Water Intrusion and Accumulation: Lessons from the Past and Recommendations for the Future, 92–112. 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959: ASTM International, 2014. http://dx.doi.org/10.1520/stp154920130042.
Full textAlexander, Paulette S. "Unsolicited Web Intrusions." In Personal Web Usage in the Workplace, 125–40. IGI Global, 2004. http://dx.doi.org/10.4018/978-1-59140-148-3.ch007.
Full text"- Network Intrusion and Security." In Windows Networking Tools, 312–57. Auerbach Publications, 2016. http://dx.doi.org/10.1201/b13093-9.
Full text"Introducing Intrusion Detection Systems and Snort." In Windows to Linux Migration Toolkit, 403–54. Elsevier, 2004. http://dx.doi.org/10.1016/b978-193183639-5/50041-2.
Full textFatemi, Mohammad Rasool, and Ali A. Ghorbani. "Threat Hunting in Windows Using Big Security Log Data." In Security, Privacy, and Forensics Issues in Big Data, 168–88. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9742-1.ch007.
Full textMondal, Soumik, Patrick Bours, Lasse Johansen, Robin Stenvi, and Magnus Øverbø. "Importance of a Versatile Logging Tool for Behavioural Biometrics and Continuous Authentication Research." In Developing Next-Generation Countermeasures for Homeland Security Threat Prevention, 282–305. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0703-1.ch013.
Full textZhu, Bonnie, and Shankar Sastry. "Intrusion Detection and Resilient Control for SCADA Systems." In Securing Critical Infrastructures and Critical Control Systems, 352–83. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2659-1.ch015.
Full textConference papers on the topic "Intrusive windows"
Alfaro, J. A., P. A. Rodríguez, A. Lecuona, R. Calle, and B. Lázaro. "Low NOx LPP Combustion Test Facility With Four Transparent Windows for Non Intrusive Flow Diagnostics." In ASME 1999 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/99-gt-297.
Full textBauer, H. J., L. Eigenmann, B. Scherrer, and S. Wittig. "Local Measurements in a Three Dimensional Jet-Stabilized Model Combustor." In ASME 1995 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/95-gt-071.
Full textCastanhel, Gabriel Ruschel, Tiago Heinrich, Fabrício Ceschin, and Carlos A. Maziero. "Sliding Window: The Impact of Trace Size in Anomaly Detection System for Containers Through Machine Learning." In XVIII Escola Regional de Redes de Computadores. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/errc.2020.15203.
Full textZoppi, Tommaso, Andrea Ceccarellli, and Andrea Bondavalli. "An Initial Investigation on Sliding Windows for Anomaly-Based Intrusion Detection." In 2019 IEEE World Congress on Services (SERVICES). IEEE, 2019. http://dx.doi.org/10.1109/services.2019.00031.
Full textSteverson, Kai, Caleb Carlin, Jonathan Mullin, and Metin Ahiskali. "Cyber Intrusion Detection using Natural Language Processing on Windows Event Logs." In 2021 International Conference on Military Communication and Information Systems (ICMCIS). IEEE, 2021. http://dx.doi.org/10.1109/icmcis52405.2021.9486307.
Full textXu, Fei, Chengyu Tan, Yi Zheng, and Ming Geng. "The Method of Classified Danger Sensed for Windows Process Intrusion Detection." In 2009 International Conference on Management of e-Commerce and e-Government. IEEE, 2009. http://dx.doi.org/10.1109/icmecg.2009.72.
Full textTobin, Donald L., and Michael S. Ware. "Using a windows attack intRusion emulator (AWARE) to teach computer security awareness." In the 10th annual SIGCSE conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1067445.1067504.
Full textChen, W. H., M. X. Ho, and Chin Pan. "Using Infrared Thermography to Study Thermal Development in the Entrance Region of a Rectangular Microchannel." In ASME 2013 Power Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/power2013-98215.
Full textNi, He Xue. "Based Sliding Window Cloud Computing Platform of Network Intrusion Detection Algorithm." In 2014 IEEE International Conference on Computer and Information Technology (CIT). IEEE, 2014. http://dx.doi.org/10.1109/cit.2014.172.
Full textLi, Shengnan, and Xiaofeng Zhou. "An Intrusion Detection Method Based on Damped Window of Data Stream Clustering." In 2017 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). IEEE, 2017. http://dx.doi.org/10.1109/ihmsc.2017.55.
Full textReports on the topic "Intrusive windows"
Andrew Freedman, Paul L. Kebabian, Richard R. Romano, and James Woodroffe. NON-INTRUSIVE SENSOR FOR GAS FILL VERIFICATION OF INSULATED GLASS WINDOWS. Office of Scientific and Technical Information (OSTI), October 2003. http://dx.doi.org/10.2172/822121.
Full text