IMPACT: Impersonation Attack Detection via Edge Computing Using Deep Autoencoder and Feature Abstraction

IMPACT: Impersonation Attack Detection via Edge Computing Using Deep Autoencoder and Feature Abstraction

An ever-increasing number of computing devices interconnected through wireless networks encapsulated in the cyber-physical-social systems and a significant amount of sensitive network data transmitted among them have raised security and privacy concerns. Intrusion detection system (IDS) is known as...

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Bibliographic Details
Main Authors: Seo Jin Lee, Paul D. Yoo, A. Taufiq Asyhari, Yoonchan Jhi, Lounis Chermak, Chan Yeob Yeun, Kamal Taha
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
IoT security
intrusion detection
feature engineering
mutual information
machine learning
edge computing
Online Access:https://ieeexplore.ieee.org/document/9055368/

Internet

https://ieeexplore.ieee.org/document/9055368/

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