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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
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
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

journal article
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
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
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
9

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 9, displaying 1 - 9

1. anomaly detection
2. anomaly detection for system logs
3. network anomaly detection
4. anomaly
5. Bouguer anomaly
6. Ce anomaly
7. cerium anomaly
8. europium anomaly
9. gravity anomaly
10. residual gravity anomaly
11. Residual Terrain Model (RTM) anomaly
12. residual terrain model anomaly
13. wind anomaly
14. amoxicillin detection
15. antibiotic detection
16. antibiotics detection
17. aspect detection
18. asynchronous fault detection
19. attack detection
20. barotrauma detection system
21. behaviour-based intrusion detection systems
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. cyber intrusion detection
36. defect detection
37. detection
38. detection efficiency
39. detection engineering
40. detection methods
41. detection of anomalous end user nodes
42. detection of hydrogen isotopes
43. distributed detection
44. early detection
45. early intrusion 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. intrusion detection
68. intrusion detection system
69. intrusion detection system (IDS)
70. intrusion detection systems
71. island detection
72. islanding detection
73. label-free detection
74. LED fluorescence detection
75. leg detection
76. light detection and ranging
77. light detection and ranging (LiDAR)
78. Light Detection and Ranging (LiDAR) point cloud
79. limit of detection
80. lock-in detection
81. loop-closure detection
82. malware detection
83. marker detection
84. mobile malware detection
85. money laundering detection systems
86. monitoring and detection
87. multi-classed object detection
88. mutant detection
89. network intrusion detection system
90. nodules detection
91. object detection
92. oil-spill detection
93. outlier’s detection methods
94. outliers detection
95. peak detection
96. plagiarism detection
97. position 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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