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anomaly detection (keyword)
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1
book article
MedBIoT : generation of an IoT Botnet Dataset in a medium-sized IoT network
Guerra Manzanares, Alejandro
;
Medina-Galindo, Jorge
;
Bahsi, Hayretdin
;
Nõmm, Sven
Proceedings of the 6th International Conference on Information Systems Security and Privacy, ICISSP : February 25-27, 2020, La Valletta, Malta. Vol. 1
2020
/
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
2
journal article
Novel real-time in-step gait anomaly detection algorithms
Rostovski, Jakob
;
Krivošei, Andrei
;
Kuusik, Alar
;
Le Moullec, Yannick
;
Alam, Muhammad Mahtab
techrxiv.org
2024
https://doi.org/10.36227/techrxiv.171173236.66440239/v1
journal article
3
book article
Real-time gait anomaly detection using 1D-CNN and LSTM
Rostovski, Jakob
;
Ahmadilivani, Mohammad Hasan
;
Krivošei, Andrei
;
Kuusik, Alar
;
Alam, Muhammad Mahtab
Digital Health and Wireless Solutions : First Nordic Conference, NCDHWS 2024, Oulu, Finland, May 7–8, 2024 : Proceedings, Part II
2024
/
p. 260-278
https://doi.org/10.1007/978-3-031-59091-7_17
book article
4
book article
Real-time gait anomaly detection using SVM time series classification
Rostovski, Jakob
;
Krivošei, Andrei
;
Kuusik, Alar
;
Alam, Muhammad Mahtab
;
Ahmadov, Ulvi
2023 International Wireless Communications and Mobile Computing (IWCMC)
2023
/
p. 1389-1394
https://doi.org/10.1109/IWCMC58020.2023.10182666
book article
5
book article
Unsupervised anomaly based botnet detection in IoT networks
Nõmm, Sven
;
Bahsi, Hayretdin
17th IEEE International Conference on Machine Learning and Applications : ICMLA 2018, 17–20 December 2018, Orlando, Florida, USA : proceedings
2018
/
p. 1048-1053
https://doi.org/10.1109/ICMLA.2018.00171
book article
6
book article EST
/
book article ENG
Using MedBIoT dataset to build effective machine learning-based IoT botnet detection systems
Guerra Manzanares, Alejandro
;
Medina-Galindo, Jorge
;
Bahsi, Hayretdin
;
Nõmm, Sven
Information Systems Security and Privacy : 6th International Conference, ICISSP 2020, Valletta, Malta, February 25–27, 2020 : revised selected papers
2022
/
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 6, displaying
1 - 6
keyword
100
1.
anomaly detection
2.
anomaly detection for system logs
3.
network anomaly detection
4.
anomaly
5.
Bouguer anomaly
6.
cerium anomaly
7.
europium anomaly
8.
gravity anomaly
9.
residual gravity anomaly
10.
Residual Terrain Model (RTM) anomaly
11.
residual terrain model anomaly
12.
wind anomaly
13.
amoxicillin detection
14.
antibiotic detection
15.
antibiotics detection
16.
asynchronous fault detection
17.
attack detection
18.
barotrauma detection system
19.
body detection
20.
botnet detection
21.
capacitively coupled conductivity detection
22.
change detection
23.
chemical detection
24.
community detection
25.
compu ter-aided detection(CAD)
26.
computer-aided detection
27.
computer‐aided detection
28.
contactless conductivity detection
29.
contactless conductivity detection (C4D)
30.
crash detection
31.
defect detection
32.
detection
33.
detection efficiency
34.
detection engineering
35.
detection of anomalous end user nodes
36.
distributed detection
37.
early detection
38.
early intrusion detection
39.
energy detection
40.
error detection
41.
ESI-MS and IM detection
42.
Event detection
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.
hepatitis C virus (HCV) detection
53.
hubs detection
54.
IED detection
55.
indicident detection and response
56.
indirect UV absorbance detection
57.
intrusion detection
58.
intrusion detection systems
59.
island detection
60.
islanding detection
61.
label-free detection
62.
LED fluorescence detection
63.
leg detection
64.
light detection and ranging
65.
Light Detection and Ranging (LiDAR) point cloud
66.
limit of detection
67.
lock-in detection
68.
loop-closure detection
69.
malware detection
70.
marker detection
71.
mobile malware detection
72.
money laundering detection systems
73.
monitoring and detection
74.
multi-classed object detection
75.
mutant detection
76.
nodules detection
77.
object detection
78.
oil-spill detection
79.
outlier’s detection methods
80.
outliers detection
81.
plagiarism detection
82.
position detection
83.
protein detection
84.
proton detection
85.
radar detection
86.
ramp event detection
87.
recycled FPGA detection
88.
robust detection
89.
short-circuit detection
90.
small molecule detection
91.
speech activity detection
92.
Suicidal ideation detection
93.
synchronous detection
94.
tyre detection
95.
unmanned aerial vehicle detection systems
96.
unsupervised outlier detection
97.
UV detection
98.
vehicle detection
99.
vortex detection
100.
3D lane detection
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