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book article

AIS data analysis: reality in the Sea of EchosVisky, Gabor; Rohl, Alexander; Katsikas, Sokratis; Maennel, Olaf Manuel2024 IEEE 49th Conference on Local Computer Networks (LCN)2024 / 7 p https://doi.org/10.1109/LCN60385.2024.10639765

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book article

Anomalous File System Activity detection through Temporal Association rule miningReza, M.; Iman, H.; Chikul, Pavel; Jervan, Gert; Bahsi, Hayretdin; Ghasempouri, TaraProceedings of the 9th International Conference on Information Systems Security and Privacy ICISSP. Vol. 12023 / p. 733-740 https://doi.org//10.5220/0000168400003405

book article
3

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
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
4

journal article

Novel real-time in-step gait anomaly detection algorithmsRostovski, Jakob; Krivošei, Andrei; Kuusik, Alar; Le Moullec, Yannick; Alam, Muhammad Mahtabtechrxiv.org2024 https://doi.org/10.36227/techrxiv.171173236.66440239/v1

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5

book article EST / book article ENG

Real-time gait anomaly detection using 1D-CNN and LSTMRostovski, Jakob; Ahmadilivani, Mohammad Hasan; Krivošei, Andrei; Kuusik, Alar; Alam, Muhammad MahtabDigital Health and Wireless Solutions : First Nordic Conference, NCDHWS 2024, Oulu, Finland, May 7–8, 2024 : Proceedings, Part II2024 / p. 260-278 https://doi.org/10.1007/978-3-031-59091-7_17 Conference proceedings at Scopus Article at Scopus Article at WOS

book article EST / book article ENG
Related publications 1
- Development of methods for real-time in-step anomaly detection in gait analysis = Reaalajaliste meetodite arendus sammusiseste kõrvalkallete tuvastamiseks kõnnianalüüsis
6

book article

Real-time gait anomaly detection using SVM time series classificationRostovski, Jakob; Krivošei, Andrei; Kuusik, Alar; Alam, Muhammad Mahtab; Ahmadov, Ulvi2023 International Wireless Communications and Mobile Computing (IWCMC)2023 / p. 1389-1394 https://doi.org/10.1109/IWCMC58020.2023.10182666

book article
Related publications 1
- Development of methods for real-time in-step anomaly detection in gait analysis = Reaalajaliste meetodite arendus sammusiseste kõrvalkallete tuvastamiseks kõnnianalüüsis
7

book article EST / book article ENG

Signature-based approach to detecting malicious outgoing trafficPetliak, Nataliia; Klots, Yurii; Titova, Vira; Cheshun, Viktor; Boyarchuk, ArtemIntelITSIS 2023: Intelligent Information Technologies & Systems of Information Security 2023 : proceedings of the 4th International Workshop on Intelligent Information Technologies & Systems of Information Security : Khmelnytskyi, Ukraine, March 22-24, 20232023 / p. 486 - 506 https://ceur-ws.org/Vol-3373/paper33.pdf Conference Proceedings at Scopus Article at Scopus

book article EST / book article ENG
8

book article

Unsupervised anomaly based botnet detection in IoT networksNõmm, Sven; Bahsi, Hayretdin17th IEEE International Conference on Machine Learning and Applications : ICMLA 2018, 17–20 December 2018, Orlando, Florida, USA : proceedings2018 / p. 1048-1053 https://doi.org/10.1109/ICMLA.2018.00171

book article
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book article

Using Incremental Inductive Logic Programming for Learning Spoofing Attacks on Maritime Automatic Identification System DataBenterki, Aboubaker Seddiq; Visky, Gabor; Vain, Jüri; Tsiopoulos, LeonidasMaritime Cybersecurity2025 / p. 123-141 https://doi.org/10.1007/978-3-031-87290-7_7

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10

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
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 10, displaying 1 - 10

1. anomaly detection
2. anomaly detection for system logs
3. network anomaly detection
4. cerium anomaly europium anomaly
5. anomaly
6. Bouguer anomaly
7. Ce anomaly
8. cerium anomaly
9. europium anomaly
10. gravity anomaly
11. residual gravity anomaly
12. Residual Terrain Model (RTM) anomaly
13. residual terrain model anomaly
14. wind anomaly
15. amoxicillin detection
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. behaviour-based intrusion detection systems
24. body detection
25. botnet detection
26. capacitively coupled conductivity detection
27. change detection
28. chemical detection
29. community detection
30. compu ter-aided detection(CAD)
31. computer-aided detection
32. computer‐aided detection
33. contactless conductivity detection
34. contactless conductivity detection (C4D)
35. crack detection
36. crash detection
37. cyber intrusion detection
38. defect detection
39. detection
40. detection efficiency
41. detection engineering
42. detection method
43. detection methods
44. detection of anomalous end user nodes
45. detection of hydrogen isotopes
46. distributed detection
47. early detection
48. early intrusion detection
49. energy detection
50. error detection
51. ESI-MS and IM detection
52. Event detection
53. extraction and detection methods
54. face detection
55. Face Manipulation Detection
56. failure detection
57. fall detection
58. fault detection
59. fault detection and diagnoses
60. fault detection and diagnosis
61. Fish detection
62. fouling detection
63. harmonic detection
64. hepatitis C virus (HCV) detection
65. hubs detection
66. IED detection
67. image-based crack detection
68. indicident detection and response
69. indirect UV absorbance detection
70. intrusion detection
71. intrusion detection system
72. intrusion detection system (IDS)
73. intrusion detection systems
74. island detection
75. islanding detection
76. label-free detection
77. lane detection
78. LED fluorescence detection
79. leg detection
80. light detection and ranging
81. light detection and ranging (LiDAR)
82. Light Detection and Ranging (LiDAR) point cloud
83. limit of detection
84. lock-in detection
85. loop-closure detection
86. malware detection
87. marker detection
88. mobile malware detection
89. money laundering detection systems
90. monitoring and detection
91. multi-classed object detection
92. Multi-valued Simulation for Hazard Detection in Digital Circuits
93. mutant detection
94. network intrusion detection system
95. nodules detection
96. object detection
97. oil-spill detection
98. outlier’s detection methods
99. outliers detection
100. peak detection
101. phytoplankton detection methods
102. plagiarism detection
103. position detection
104. precursor detection
105. protein detection
106. proton detection
107. radar detection
108. ramp event detection
109. recycled FPGA detection
110. residual current detection
111. robust detection
112. scene text detection
113. short-circuit detection
114. small molecule detection
115. speech activity detection
116. Suicidal ideation detection
117. synchronous detection
118. tyre detection
119. unmanned aerial vehicle detection systems
120. unsupervised outlier detection
121. UV detection
122. vehicle detection
123. vortex detection
124. 3D lane detection

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