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intrusion detection (keyword)
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1
book article
Deep learning-based detection of cyberattacks in software-defined networks
Mirsadeghi, Seyed Mohammad Hadi
;
Bahsi, Hayretdin
;
Inbouli, Wissem
Digital forensics and cyber crime : 13th EAI international conference, ICDF2C 2022, Boston, MA, November 16-18, 2022 : proceedings
2023
/
p. 341-354
https://doi.org/10.1007/978-3-031-36574-4_20
book article
2
book article
Dimensionality reduction for machine learning based IoT botnet detection
Bahsi, Hayretdin
;
Nõmm, Sven
15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018) : Singapore, November 18-21, 2018
2018
/
p. 1857-1862 : ill
https://doi.org/10.1109/ICARCV.2018.8581205
book article
3
journal article EST
/
journal article ENG
In-depth feature selection for the statistical machine learning-based botnet detection in IoT networks
Kalakoti, Rajesh
;
Nõmm, Sven
;
Bahsi, Hayretdin
IEEE Access
2022
/
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
journal article EST
/
journal article ENG
4
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
5
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 5, displaying
1 - 5
keyword
102
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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