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intrusion detection (võtmesõna)

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Kirjeid leitud 11
Vaata veel.. (1/130)
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1

artikkel kogumikus

Comprehensive Feature Selection for Machine Learning-Based Intrusion Detection in Healthcare IoMT NetworksRehman, Muaan Ur; Kalakoti, Rajesh; Bahsi, HayretdinProceedings of the 11th International Conference on Information Systems Security and Privacy (ICISSP 2025). Vol. 22025 / p. 248-259 : ill https://www.scitepress.org/Papers/2025/133136/133136.pdf https://doi.org//10.5220/0013313600003899

artikkel kogumikus
Seotud publikatsioonid 1
- Explainable artificial intelligence-based intrusion detection systems = Selgitaval tehisintellektil baseeruvad ründetuvastussüsteemid
2

artikkel kogumikus

Deep learning-based detection of cyberattacks in software-defined networksMirsadeghi, Seyed Mohammad Hadi; Bahsi, Hayretdin; Inbouli, WissemDigital forensics and cyber crime : 13th EAI international conference, ICDF2C 2022, Boston, MA, November 16-18, 2022 : proceedings2023 / p. 341-354 https://doi.org/10.1007/978-3-031-36574-4_20

artikkel kogumikus
3

artikkel kogumikus

Dimensionality reduction for machine learning based IoT botnet detectionBahsi, Hayretdin; Nõmm, Sven15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018) : Singapore, November 18-21, 20182018 / p. 1857-1862 : ill https://doi.org/10.1109/ICARCV.2018.8581205

artikkel kogumikus
4

artikkel kogumikus

Explainable federated learning for Botnet Detection in IoT networksKalakoti, Rajesh; Bahsi, Hayretdin; Nõmm, SvenProceedings of the 2024 IEEE International Conference on Cyber Security and Resilience (CSR), September 2-4, 2024, London, UK2024 / p. 22-29 https://doi.org/10.1109/CSR61664.2024.10679348 Article at Scopus Article at WOS

artikkel kogumikus
Seotud publikatsioonid 1
- Explainable artificial intelligence-based intrusion detection systems = Selgitaval tehisintellektil baseeruvad ründetuvastussüsteemid
5

artikkel ajakirjas

Federated Learning of Explainable AI(FedXAI) for deep learning-based intrusion detection in IoT networksKalakoti, Rajesh; Nõmm, Sven; Bahsi, HayretdinComputer networks2025 / art. 111479, 23 p. : ill https://doi.org/10.1016/j.comnet.2025.111479

artikkel ajakirjas
Seotud publikatsioonid 1
- Explainable artificial intelligence-based intrusion detection systems = Selgitaval tehisintellektil baseeruvad ründetuvastussüsteemid
6

artikkel ajakirjas EST / artikkel ajakirjas ENG

In-depth feature selection for the statistical machine learning-based botnet detection in IoT networksKalakoti, Rajesh; Nõmm, Sven; Bahsi, HayretdinIEEE Access2022 / p. 94518-94535 https://doi.org/10.1109/ACCESS.2022.3204001 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
Seotud publikatsioonid 1
- Explainable artificial intelligence-based intrusion detection systems = Selgitaval tehisintellektil baseeruvad ründetuvastussüsteemid
7

artikkel ajakirjas EST / artikkel ajakirjas ENG

LSPR23: A novel IDS dataset from the largest live-fire cybersecurity exerciseDijk, Allard; Halisdemir, Emre; Melella, Cosimo; Schu, Alari; Pihelgas, Mauno; Meier, RolandJournal of Information Security and Applications2024 / art. 103847, 14, p. : ill https://doi.org/10.1016/j.jisa.2024.103847 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
8

artikkel kogumikus

MedBIoT : generation of an IoT Botnet Dataset in a medium-sized IoT networkGuerra Manzanares, Alejandro; Medina-Galindo, Jorge; Bahsi, Hayretdin; Nõmm, SvenProceedings of the 6th International Conference on Information Systems Security and Privacy, ICISSP : February 25-27, 2020, La Valletta, Malta. Vol. 12020 / p. 207-218 : ill https://doi.org/10.5220/0009187802070218

artikkel kogumikus
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
9

artikkel ajakirjas EST / artikkel ajakirjas ENG

Stream clustering guided supervised learning for classifying NIDS alertsVaarandi, Risto; Guerra Manzanares, AlejandroFuture generation computer systems2024 / p. 231-244 : ill https://doi.org/10.1016/j.future.2024.01.032 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
10

artikkel ajakirjas EST / artikkel ajakirjas ENG

A systematic literature review of cyber security monitoring in maritimeVaarandi, Risto; Tsiopoulos, Leonidas; Visky, Gabor; Rehman, Muaan Ur; Bahsi, HayretdinIEEE Access2025 / p. 85307-85329 https://doi.org/10.1109/ACCESS.2025.3567385 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
Seotud publikatsioonid 1
- Cybersecurity for maritime operational technology: challenges, considerations, and solutions = Merendustehnoloogia küberturvalisus: väljakutsed, kaalutlused ja lahendused
11

artikkel kogumikus EST / artikkel kogumikus ENG

Using MedBIoT dataset to build effective machine learning-based IoT botnet detection systemsGuerra Manzanares, Alejandro; Medina-Galindo, Jorge; Bahsi, Hayretdin; Nõmm, SvenInformation Systems Security and Privacy : 6th International Conference, ICISSP 2020, Valletta, Malta, February 25–27, 2020 : revised selected papers2022 / p. 222–243 https://doi.org/10.1007/978-3-030-94900-6_11 Conference proceedings at Scopus Article at Scopus Article at WOS

artikkel kogumikus EST / artikkel kogumikus ENG
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks

Kirjeid leitud 11, kuvan 1 - 11

1. behaviour-based intrusion detection systems
2. cyber intrusion detection
3. early intrusion detection
4. evaluation of explainable AI intrusion detection
5. health care IoMT intrusion detection
6. intrusion detection
7. intrusion detection system (IDS)
8. intrusion detection systems
9. intrusion detection systems (IDS)
10. network intrusion detection system
11. air intrusion
12. intrusion
13. intrusion response system
14. saline intrusion blockage
15. AI-based fault detection
16. amoxicillin detection
17. anomaly detection
18. anomaly detection for system logs
19. antibiotic detection
20. antibiotics detection
21. aspect detection
22. asynchronous fault detection
23. attack detection
24. barotrauma detection system
25. Barotrauma detection system sensors
26. body detection
27. botnet detection
28. capacitively coupled conductivity detection
29. change detection
30. chemical detection
31. community detection
32. compu ter-aided detection(CAD)
33. computer-aided detection
34. computer‐aided detection
35. contactless conductivity detection
36. contactless conductivity detection (C4D)
37. crack detection
38. crash detection
39. defect detection
40. detection
41. detection efficiency
42. detection engineering
43. detection mechanisms
44. detection method
45. detection methods
46. detection of anomalous end user nodes
47. detection of hydrogen isotopes
48. distributed detection
49. early detection
50. electronic warfare activity detection
51. energy detection
52. error detection
53. ESI-MS and IM detection
54. Event detection
55. extraction and detection methods
56. face detection
57. Face Manipulation Detection
58. failure detection
59. fall detection
60. fault detection
61. fault detection and classification
62. fault detection and diagnoses
63. fault detection and diagnosis
64. fault detection and diagnostics (FDD)
65. Fish detection
66. fouling detection
67. harmonic detection
68. hepatitis C virus (HCV) detection
69. hubs detection
70. hybrid fault detection
71. IED detection
72. image-based crack detection
73. indicident detection and response
74. indirect UV absorbance detection
75. island detection
76. islanding detection
77. label-free detection
78. lane detection
79. lane line detection
80. LED fluorescence detection
81. leg detection
82. light detection and ranging
83. light detection and ranging (LiDAR)
84. Light Detection and Ranging (LiDAR) point cloud
85. limit of detection
86. lock-in detection
87. loop-closure detection
88. malware detection
89. marker detection
90. mobile malware detection
91. money laundering detection systems
92. monitoring and detection
93. multi-classed object detection
94. Multi-valued Simulation for Hazard Detection in Digital Circuits
95. mutant detection
96. network anomaly detection
97. nodules detection
98. object detection
99. oil-spill detection
100. outlier’s detection methods
101. outliers detection
102. peak detection
103. photovoltaic fault detection algorithms
104. phytoplankton detection methods
105. plagiarism detection
106. position detection
107. precursor detection
108. propaganda detection
109. protein detection
110. proton detection
111. radar detection
112. ramp event detection
113. recycled FPGA detection
114. residual current detection
115. robust detection
116. scene text detection
117. short-circuit detection
118. Side-Channel Attack Detection
119. small molecule detection
120. speech activity detection
121. Suicidal ideation detection
122. synchronous detection
123. topic detection
124. tyre detection
125. unmanned aerial vehicle detection systems
126. unsupervised outlier detection
127. UV detection
128. vehicle detection
129. vortex detection
130. 3D lane detection

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