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Detecting Botnet Attacks in IoT Environments: An Optimized Machine
  Learning Approach

Detecting Botnet Attacks in IoT Environments: An Optimized Machine Learning Approach

16 December 2020
MohammadNoor Injadat
Abdallah Moubayed
Abdallah Shami
ArXivPDFHTML

Papers citing "Detecting Botnet Attacks in IoT Environments: An Optimized Machine Learning Approach"

6 / 6 papers shown
Title
Optimized Ensemble Model Towards Secured Industrial IoT Devices
Optimized Ensemble Model Towards Secured Industrial IoT Devices
MohammadNoor Injadat
45
2
0
10 Jan 2024
LE3D: A Lightweight Ensemble Framework of Data Drift Detectors for
  Resource-Constrained Devices
LE3D: A Lightweight Ensemble Framework of Data Drift Detectors for Resource-Constrained Devices
Ioannis Mavromatis
Adrián Sánchez-Mompó
Francesco Raimondo
James Pope
Marcello Bullo
...
Vijay S. Kumar
P. Carnelli
G. Oikonomou
Theodoros Spyridopoulos
Aftab Khan
32
5
0
03 Nov 2022
Anomaly Detection in Intra-Vehicle Networks
Anomaly Detection in Intra-Vehicle Networks
A. Dwivedi
33
3
0
07 May 2022
A Method Based on Deep Learning for the Detection and Characterization
  of Cybersecurity Incidents in Internet of Things Devices
A Method Based on Deep Learning for the Detection and Characterization of Cybersecurity Incidents in Internet of Things Devices
Jhon Alexánder Parra
S. Gutiérrez
J. Branch
26
2
0
01 Mar 2022
A Lightweight Concept Drift Detection and Adaptation Framework for IoT
  Data Streams
A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams
Li Yang
Abdallah Shami
61
103
0
21 Apr 2021
Relationship between Student Engagement and Performance in e-Learning
  Environment Using Association Rules
Relationship between Student Engagement and Performance in e-Learning Environment Using Association Rules
Abdallah Moubayed
MohammadNoor Injadat
Abdallah Shami
H. Lutfiyya
55
39
0
25 Dec 2020
1