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intrusion detection (võtmesõna)

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Kirjeid leitud 11
Vaata veel.. (1/135)
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ekspordi kõik päringu tulemused (11)
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1

artikkel kogumikus EST / artikkel kogumikus ENG

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 Conference proceedings at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel kogumikus EST / artikkel kogumikus ENG
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 EST / artikkel ajakirjas ENG

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 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
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. dementia detection
41. detection
42. detection efficiency
43. detection engineering
44. detection mechanisms
45. detection method
46. detection methods
47. detection of anomalous end user nodes
48. detection of hydrogen isotopes
49. distributed detection
50. early detection
51. electronic warfare activity detection
52. energy detection
53. error detection
54. ESI-MS and IM detection
55. Event detection
56. extraction and detection methods
57. face detection
58. Face Manipulation Detection
59. failure detection
60. fall detection
61. fault detection
62. fault detection and classification
63. fault detection and diagnoses
64. fault detection and diagnosis
65. fault detection and diagnostics (FDD)
66. Fish detection
67. fouling detection
68. hardware trojan detection
69. harmonic detection
70. hepatitis C virus (HCV) detection
71. hubs detection
72. hybrid fault detection
73. IED detection
74. image-based crack detection
75. indicident detection and response
76. indirect UV absorbance detection
77. island detection
78. islanding detection
79. label-free detection
80. lane detection
81. lane line detection
82. LED fluorescence detection
83. leg detection
84. light detection and ranging
85. light detection and ranging (LiDAR)
86. Light Detection and Ranging (LiDAR) point cloud
87. limit of detection
88. LLM-based template detection from security event logs
89. lock-in detection
90. loop-closure detection
91. malware detection
92. marker detection
93. mobile malware detection
94. molecular detection
95. money laundering detection systems
96. monitoring and detection
97. multi-classed object detection
98. Multi-valued Simulation for Hazard Detection in Digital Circuits
99. mutant detection
100. network anomaly detection
101. nodules detection
102. object detection
103. oil-spill detection
104. outlier’s detection methods
105. outliers detection
106. peak detection
107. photovoltaic fault detection algorithms
108. phytoplankton detection methods
109. plagiarism detection
110. position detection
111. precursor detection
112. propaganda detection
113. protein detection
114. proton detection
115. radar detection
116. ramp event detection
117. recycled FPGA detection
118. residual current detection
119. robust detection
120. scene text detection
121. short-circuit detection
122. Side-Channel Attack Detection
123. small molecule detection
124. speech activity detection
125. Suicidal ideation detection
126. synchronous detection
127. Template detection from event logs
128. topic detection
129. tyre detection
130. unmanned aerial vehicle detection systems
131. unsupervised outlier detection
132. UV detection
133. vehicle detection
134. vortex detection
135. 3D lane detection

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