Scalable machine learning-based intrusion detection system for IoT-enabled smart cities
Given a scale expansion of Internet of Things for sustainable resource management in smart cities, proper design of an intrusion detection system (IDS) is critical to safeguard the future network infrastructure from intruders. With the growth of connected things, the most-widely used centralized (cl...
Main Authors: | Rahman, Md. Arafatur, Asyhari, A. Taufiq, Leong, L. S., Satrya, G. B., Tao, M. Hai, Mohamad Fadli, Zolkipli |
---|---|
Format: | Article |
Language: | English English |
Published: |
Elsevier Ltd
2020
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/28942/1/Scalable%20machine%20learning-based%20intrusion%20detection%20system%20for%20IoT_FULL.pdf http://umpir.ump.edu.my/id/eprint/28942/2/Scalable%20machine%20learning-based%20intrusion%20detection%20system%20for%20IoT.pdf |
Similar Items
-
A scalable hybrid MAC strategy for traffic-differentiated IoT-enabled intra-vehicular networks
by: Rahman, Md. Arafatur, et al.
Published: (2020) -
A framework of IoT-enabled vehicular noise intensity monitoring system for smart city
by: Rahim, Md. Abdur, et al.
Published: (2021) -
The emergence of internet of things (IoT) : connecting anything, anywhere
by: Rahman, Md. Arafatur, et al.
Published: (2019) -
IoT-enabled smart cities towards green energy systems: A review
by: Ajra, Husnul, et al.
Published: (2024) -
IoT-Enabled Light Intensity-Controlled Seamless Highway Lighting System
by: Rahman, Md. Arafatur, et al.
Published: (2020)