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

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