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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

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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

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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

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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

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5

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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

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book article

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

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Related publications 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
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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

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8

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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

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9

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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

book article EST / book article ENG
Related publications 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

Number of records 9, displaying 1 - 9

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

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