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book article

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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book article

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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journal article EST / journal article 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

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5

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

book article
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
6

journal article EST / journal article 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

journal article EST / journal article ENG
7

book article EST / book article 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

book article EST / book article 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

Number of records 7, displaying 1 - 7

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. body detection
23. botnet detection
24. capacitively coupled conductivity detection
25. change detection
26. chemical detection
27. community detection
28. compu ter-aided detection(CAD)
29. computer-aided detection
30. computer‐aided detection
31. contactless conductivity detection
32. contactless conductivity detection (C4D)
33. crack detection
34. crash detection
35. defect detection
36. detection
37. detection efficiency
38. detection engineering
39. detection methods
40. detection of anomalous end user nodes
41. detection of hydrogen isotopes
42. distributed detection
43. early detection
44. energy detection
45. error detection
46. ESI-MS and IM detection
47. Event detection
48. extraction and detection methods
49. face detection
50. Face Manipulation Detection
51. failure detection
52. fall detection
53. fault detection
54. fault detection and diagnoses
55. fault detection and diagnosis
56. Fish detection
57. fouling detection
58. harmonic detection
59. hepatitis C virus (HCV) detection
60. hubs detection
61. IED detection
62. image-based crack detection
63. indicident detection and response
64. indirect UV absorbance detection
65. island detection
66. islanding detection
67. label-free detection
68. LED fluorescence detection
69. leg detection
70. light detection and ranging
71. light detection and ranging (LiDAR)
72. Light Detection and Ranging (LiDAR) point cloud
73. limit of detection
74. lock-in detection
75. loop-closure detection
76. malware detection
77. marker detection
78. mobile malware detection
79. money laundering detection systems
80. monitoring and detection
81. multi-classed object detection
82. mutant detection
83. network anomaly detection
84. nodules detection
85. object detection
86. oil-spill detection
87. outlier’s detection methods
88. outliers detection
89. peak detection
90. plagiarism detection
91. position detection
92. protein detection
93. proton detection
94. radar detection
95. ramp event detection
96. recycled FPGA detection
97. residual current detection
98. robust detection
99. scene text detection
100. short-circuit detection
101. small molecule detection
102. speech activity detection
103. Suicidal ideation detection
104. synchronous detection
105. tyre detection
106. unmanned aerial vehicle detection systems
107. unsupervised outlier detection
108. UV detection
109. vehicle detection
110. vortex detection
111. 3D lane detection

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