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intrusion detection (võtmesõna)

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Kirjeid leitud 5
Vaata veel.. (1/102)
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ekspordi kõik päringu tulemused (5)
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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
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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
3

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

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4

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
5

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 5, kuvan 1 - 5

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

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