Artykuły w czasopismach na temat „Ids and devices”
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Naz, Naila, Muazzam A. Khan, Suliman A. Alsuhibany, Muhammad Diyan, Zhiyuan Tan, Muhammad Almas Khan i Jawad Ahmad. "Ensemble learning-based IDS for sensors telemetry data in IoT networks". Mathematical Biosciences and Engineering 19, nr 10 (2022): 10550–80. http://dx.doi.org/10.3934/mbe.2022493.
Pełny tekst źródłaDat-Thinh, Nguyen, Ho Xuan-Ninh i Le Kim-Hung. "MidSiot: A Multistage Intrusion Detection System for Internet of Things". Wireless Communications and Mobile Computing 2022 (21.02.2022): 1–15. http://dx.doi.org/10.1155/2022/9173291.
Pełny tekst źródłaGluskin, Efim. "APS Insertion Devices: Recent Developments and Results". Journal of Synchrotron Radiation 5, nr 3 (1.05.1998): 189–95. http://dx.doi.org/10.1107/s0909049597013769.
Pełny tekst źródłaMatebesi, Unopa, i Nonofo M. J. Ditshego. "Indium Gallium Zinc Oxide FinFET Compared with Silicon FinFET". Journal of Nano Research 68 (29.06.2021): 103–13. http://dx.doi.org/10.4028/www.scientific.net/jnanor.68.103.
Pełny tekst źródłaLevichev, Eugene, i Nikolay Vinokurov. "Undulators and Other Insertion Devices". Reviews of Accelerator Science and Technology 03, nr 01 (styczeń 2010): 203–20. http://dx.doi.org/10.1142/s1793626810000403.
Pełny tekst źródłaCortese, Yvonne J., Victoria E. Wagner, Morgan Tierney, Declan Devine i Andrew Fogarty. "Review of Catheter-Associated Urinary Tract Infections and In Vitro Urinary Tract Models". Journal of Healthcare Engineering 2018 (14.10.2018): 1–16. http://dx.doi.org/10.1155/2018/2986742.
Pełny tekst źródłaR. Zarzoor, Ahmed, Nadia Adnan Shiltagh Al-Jamali i Dina A. Abdul Qader. "Intrusion detection method for internet of things based on the spiking neural network and decision tree method". International Journal of Electrical and Computer Engineering (IJECE) 13, nr 2 (1.04.2023): 2278. http://dx.doi.org/10.11591/ijece.v13i2.pp2278-2288.
Pełny tekst źródłaKimbrough, Joevonte, Lauren Williams, Qunying Yuan i Zhigang Xiao. "Dielectrophoresis-Based Positioning of Carbon Nanotubes for Wafer-Scale Fabrication of Carbon Nanotube Devices". Micromachines 12, nr 1 (25.12.2020): 12. http://dx.doi.org/10.3390/mi12010012.
Pełny tekst źródłaAlsharif, Maram, i Danda B. Rawat. "Study of Machine Learning for Cloud Assisted IoT Security as a Service". Sensors 21, nr 4 (3.02.2021): 1034. http://dx.doi.org/10.3390/s21041034.
Pełny tekst źródłaJaved, Abbas, Amna Ehtsham, Muhammad Jawad, Muhammad Naeem Awais, Ayyaz-ul-Haq Qureshi i Hadi Larijani. "Implementation of Lightweight Machine Learning-Based Intrusion Detection System on IoT Devices of Smart Homes". Future Internet 16, nr 6 (5.06.2024): 200. http://dx.doi.org/10.3390/fi16060200.
Pełny tekst źródłaMyridakis, Dimitrios, Georgios Spathoulas, Athanasios Kakarountas i Dimitrios Schinianakis. "Smart Devices Security Enhancement via Power Supply Monitoring". Future Internet 12, nr 3 (10.03.2020): 48. http://dx.doi.org/10.3390/fi12030048.
Pełny tekst źródłaAlsharif, Nada Abdu, Shailendra Mishra i Mohammed Alshehri. "IDS in IoT using Machine Learning and Blockchain". Engineering, Technology & Applied Science Research 13, nr 4 (9.08.2023): 11197–203. http://dx.doi.org/10.48084/etasr.5992.
Pełny tekst źródłaRani, K. Swapna, Gayatri Parasa, D. Hemanand, S. V. Devika, S. Balambigai, M. I. Thariq Hussan, Koppuravuri Gurnadha Gupta, Y. J. Nagendra Kumar i Alok Jain. "Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things". MATEC Web of Conferences 392 (2024): 01106. http://dx.doi.org/10.1051/matecconf/202439201106.
Pełny tekst źródłaKaushik, Sunil, Akashdeep Bhardwaj, Abdullah Alomari, Salil Bharany, Amjad Alsirhani i Mohammed Mujib Alshahrani. "Efficient, Lightweight Cyber Intrusion Detection System for IoT Ecosystems Using MI2G Algorithm". Computers 11, nr 10 (20.09.2022): 142. http://dx.doi.org/10.3390/computers11100142.
Pełny tekst źródłaOtoum, Safa, Burak Kantarci i Hussein Mouftah. "A Comparative Study of AI-Based Intrusion Detection Techniques in Critical Infrastructures". ACM Transactions on Internet Technology 21, nr 4 (22.07.2021): 1–22. http://dx.doi.org/10.1145/3406093.
Pełny tekst źródłaLiu, Xinzhong, Shouzhi Xuan, Shunqiang Tian, Xu Wu, Yihao Gong, Liyuan Tan i Guangwei Jiao. "Orbit stabilization for the new insertion devices in SSRF". Journal of Instrumentation 19, nr 01 (1.01.2024): T01003. http://dx.doi.org/10.1088/1748-0221/19/01/t01003.
Pełny tekst źródłaChavanne, Joel, Pascal Elleaume i Pierre Van Vaerenbergh. "The ESRF Insertion Devices". Journal of Synchrotron Radiation 5, nr 3 (1.05.1998): 196–201. http://dx.doi.org/10.1107/s0909049597012855.
Pełny tekst źródłaAdefemi Alimi, Kuburat Oyeranti, Khmaies Ouahada, Adnan M. Abu-Mahfouz, Suvendi Rimer i Oyeniyi Akeem Alimi. "Refined LSTM Based Intrusion Detection for Denial-of-Service Attack in Internet of Things". Journal of Sensor and Actuator Networks 11, nr 3 (1.07.2022): 32. http://dx.doi.org/10.3390/jsan11030032.
Pełny tekst źródłaNajam, Faraz, i Yun Seop Yu. "Compact Trap-Assisted-Tunneling Model for Line Tunneling Field-Effect-Transistor Devices". Applied Sciences 10, nr 13 (28.06.2020): 4475. http://dx.doi.org/10.3390/app10134475.
Pełny tekst źródłaCatillo, Marta, Antonio Pecchia i Umberto Villano. "A Deep Learning Method for Lightweight and Cross-Device IoT Botnet Detection". Applied Sciences 13, nr 2 (7.01.2023): 837. http://dx.doi.org/10.3390/app13020837.
Pełny tekst źródłaUmar, Umar, Kamaluddeen Usman .., Mohd Fadzil Hassan, Aminu Aminu Muazu i M. S. Liew. "An IoT Device-Level Vulnerability Control Model Through Federated Detection". Journal of Intelligent Systems and Internet of Things 12, nr 2 (2024): 89–98. http://dx.doi.org/10.54216/jisiot.120207.
Pełny tekst źródłaRomeo, M. D. Shakhawat Shafaet. "Intrusion Detection System (IDS) in Internet of Things (IoT) Devices for Smart Home". International Journal of Psychosocial Rehabilitation 23, nr 4 (20.12.2019): 1217–27. http://dx.doi.org/10.37200/ijpr/v23i4/pr190448.
Pełny tekst źródłaIsong, Bassey, Otshepeng Kgote i Adnan Abu-Mahfouz. "Insights into Modern Intrusion Detection Strategies for Internet of Things Ecosystems". Electronics 13, nr 12 (17.06.2024): 2370. http://dx.doi.org/10.3390/electronics13122370.
Pełny tekst źródłaAlsulami, Rehab, Batoul Alqarni, Rawan Alshomrani, Fatimah Mashat i Tahani Gazdar. "IoT Protocol-Enabled IDS based on Machine Learning". Engineering, Technology & Applied Science Research 13, nr 6 (5.12.2023): 12373–80. http://dx.doi.org/10.48084/etasr.6421.
Pełny tekst źródłaChen, Chii-Wen, Mu-Chun Wang, Cheng-Hsun-Tony Chang, Wei-Lun Chu, Shun-Ping Sung i Wen-How Lan. "Hot Carrier Stress Sensing Bulk Current for 28 nm Stacked High-k nMOSFETs". Electronics 9, nr 12 (8.12.2020): 2095. http://dx.doi.org/10.3390/electronics9122095.
Pełny tekst źródłaHsu, Che-Wei, Yueh-Chin Lin, Ming-Wen Lee i Edward-Yi Chang. "Investigation of the Effect of Different SiNx Thicknesses on the Characteristics of AlGaN/GaN High-Electron-Mobility Transistors in Ka-Band". Electronics 12, nr 20 (19.10.2023): 4336. http://dx.doi.org/10.3390/electronics12204336.
Pełny tekst źródłaYas, Harith, i Manal M. Nasir. "Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network". Journal of Cybersecurity and Information Management 1, nr 1 (2020): 30–37. http://dx.doi.org/10.54216/jcim.010105.
Pełny tekst źródłaKaramollaoğlu, Hamdullah, İbrahim Alper Doğru i İbrahim Yücedağ. "An Efficient Deep Learningbased Intrusion Detection System for Internet of Things Networks with Hybrid Feature Reduction and Data Balancing Techniques". Information Technology and Control 53, nr 1 (22.03.2024): 243–61. http://dx.doi.org/10.5755/j01.itc.53.1.34933.
Pełny tekst źródłaAl-Dhuhli, Maha Abullah, Ammar Khamis Al-Mizaini, Miysaa Salim Al-Braiki i Rajesh Natarajan. "Intrusion detection system to advance IoT security environment". International Journal of Information Technology, Research and Applications 2, nr 2 (22.06.2023): 10–17. http://dx.doi.org/10.59461/ijitra.v2i2.48.
Pełny tekst źródłaZhang, Yang, Yu Tang, Chaoyang Li, Hua Zhang i Haseeb Ahmad. "Post-Quantum Secure Identity-Based Signature Scheme with Lattice Assumption for Internet of Things Networks". Sensors 24, nr 13 (27.06.2024): 4188. http://dx.doi.org/10.3390/s24134188.
Pełny tekst źródłaKhan, Zeeshan Ali, i Ubaid Abbasi. "Reputation Management Using Honeypots for Intrusion Detection in the Internet of Things". Electronics 9, nr 3 (29.02.2020): 415. http://dx.doi.org/10.3390/electronics9030415.
Pełny tekst źródłaSahu, Dipti Prava, Biswajit Tripathy i Leena Samantaray. "Optimized Intrusion Detection System in Fog Computing Environment Using Automatic Termination-based Whale Optimization with ELM". International Journal of Computer Network and Information Security 16, nr 2 (8.04.2024): 79–91. http://dx.doi.org/10.5815/ijcnis.2024.02.07.
Pełny tekst źródłaIdrissi, Idriss, Mohammed Boukabous, Mostafa Azizi, Omar Moussaoui i Hakim El Fadili. "Toward a deep learning-based intrusion detection system for IoT against botnet attacks". IAES International Journal of Artificial Intelligence (IJ-AI) 10, nr 1 (1.03.2021): 110. http://dx.doi.org/10.11591/ijai.v10.i1.pp110-120.
Pełny tekst źródłaMaidamwar, Priya R., Prasad P. Lokulwar i Kailash Kumar. "Ensemble Learning Approach for Classification of Network Intrusion Detection in IoT Environment". International Journal of Computer Network and Information Security 15, nr 3 (8.06.2013): 30–36. http://dx.doi.org/10.5815/ijcnis.2023.03.03.
Pełny tekst źródłaMeliboev, Azizjon. "IOT NETWORK INTRUSION DETECTION SYSTEM USING MACHINE LEARNING TECHNIQUES". QO‘QON UNIVERSITETI XABARNOMASI 11 (30.06.2024): 112–15. http://dx.doi.org/10.54613/ku.v11i11.972.
Pełny tekst źródłaAlsamiri, Jadil, i Khalid Alsubhi. "Federated Learning for Intrusion Detection Systems in Internet of Vehicles: A General Taxonomy, Applications, and Future Directions". Future Internet 15, nr 12 (14.12.2023): 403. http://dx.doi.org/10.3390/fi15120403.
Pełny tekst źródłaKhan, Ajmal, Adnan Munir, Zeeshan Kaleem, Farman Ullah, Muhammad Bilal, Lewis Nkenyereye, Shahen Shah, Long D. Nguyen, S. M. Riazul Islam i Kyung-Sup Kwak. "RDSP: Rapidly Deployable Wireless Ad Hoc System for Post-Disaster Management". Sensors 20, nr 2 (19.01.2020): 548. http://dx.doi.org/10.3390/s20020548.
Pełny tekst źródłaNazir, Anjum, Zulfiqar Memon, Touseef Sadiq, Hameedur Rahman i Inam Ullah Khan. "A Novel Feature-Selection Algorithm in IoT Networks for Intrusion Detection". Sensors 23, nr 19 (28.09.2023): 8153. http://dx.doi.org/10.3390/s23198153.
Pełny tekst źródłaZegarra Rodríguez, Demóstenes, Ogobuchi Daniel Okey, Siti Sarah Maidin, Ekikere Umoren Udo i João Henrique Kleinschmidt. "Attentive transformer deep learning algorithm for intrusion detection on IoT systems using automatic Xplainable feature selection". PLOS ONE 18, nr 10 (16.10.2023): e0286652. http://dx.doi.org/10.1371/journal.pone.0286652.
Pełny tekst źródłaTitov, D. N. "Detection of intrusions into the Internet of things system". Interexpo GEO-Siberia 8, nr 2 (18.05.2022): 118–25. http://dx.doi.org/10.33764/2618-981x-2022-8-2-118-125.
Pełny tekst źródłaElangovan, Surya, Stone Cheng i Edward Yi Chang. "Reliability Characterization of Gallium Nitride MIS-HEMT Based Cascode Devices for Power Electronic Applications". Energies 13, nr 10 (21.05.2020): 2628. http://dx.doi.org/10.3390/en13102628.
Pełny tekst źródłaIdrissi, Idriss, Mostafa Azizi i Omar Moussaoui. "An unsupervised generative adversarial network based-host intrusion detection system for internet of things devices". Indonesian Journal of Electrical Engineering and Computer Science 25, nr 2 (1.02.2022): 1140. http://dx.doi.org/10.11591/ijeecs.v25.i2.pp1140-1150.
Pełny tekst źródłaPark, Sohyun, i Suphee Sun. ""A Study on The Direction of Sleep-Tech Devices for Middle-aged Women :Focusing on preferences for device types and function"". Journal of Industrial Design Studies 14, nr 4 (31.12.2020): 51–60. http://dx.doi.org/10.37254/ids.2020.12.54.05.51.
Pełny tekst źródłaMahmod, Md Jubayer al, i Ujjwal Guin. "A Robust, Low-Cost and Secure Authentication Scheme for IoT Applications". Cryptography 4, nr 1 (8.03.2020): 8. http://dx.doi.org/10.3390/cryptography4010008.
Pełny tekst źródłaPamungkas, I. Gede Agung Krisna, Tohari Ahmad i Royyana Muslim Ijtihadie. "Analysis of Autoencoder Compression Performance in Intrusion Detection System". International Journal of Safety and Security Engineering 12, nr 3 (30.06.2022): 395–401. http://dx.doi.org/10.18280/ijsse.120314.
Pełny tekst źródłaLong, S. B., Zhi Gang Li, X. W. Zhao, Bao Qin Chen i Ming Liu. "Coulomb Staircases and Differential Conductance Oscillations in a SIMOX-Based Single-Electron Transistor". Solid State Phenomena 121-123 (marzec 2007): 513–16. http://dx.doi.org/10.4028/www.scientific.net/ssp.121-123.513.
Pełny tekst źródłaNgo, Duc-Minh, Dominic Lightbody, Andriy Temko, Cuong Pham-Quoc, Ngoc-Thinh Tran, Colin C. Murphy i Emanuel Popovici. "HH-NIDS: Heterogeneous Hardware-Based Network Intrusion Detection Framework for IoT Security". Future Internet 15, nr 1 (26.12.2022): 9. http://dx.doi.org/10.3390/fi15010009.
Pełny tekst źródłaMusleh, Dhiaa, Meera Alotaibi, Fahd Alhaidari, Atta Rahman i Rami M. Mohammad. "Intrusion Detection System Using Feature Extraction with Machine Learning Algorithms in IoT". Journal of Sensor and Actuator Networks 12, nr 2 (29.03.2023): 29. http://dx.doi.org/10.3390/jsan12020029.
Pełny tekst źródłaJo, Wooyeon, Sungjin Kim, Changhoon Lee i Taeshik Shon. "Packet Preprocessing in CNN-Based Network Intrusion Detection System". Electronics 9, nr 7 (16.07.2020): 1151. http://dx.doi.org/10.3390/electronics9071151.
Pełny tekst źródłaNaithani, Kanchan. "AI-based Intrusion Detection System for Internet of Things (IoT) Networks". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 10, nr 2 (10.09.2019): 1095–100. http://dx.doi.org/10.17762/turcomat.v10i2.13631.
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