DeepAI AI Chat
Log In Sign Up

LocKedge: Low-Complexity Cyberattack Detection in IoT Edge Computing

by   Truong Thu Huong, et al.

Internet of Things and its applications are becoming commonplace with more devices, but always at risk of network security. It is therefore crucial for an IoT network design to identify attackers accurately, quickly and promptly. Many solutions have been proposed, mainly concerning secure IoT architectures and classification algorithms, but none of them have paid enough attention to reducing the complexity. Our proposal in this paper is an edge cloud architecture that fulfills the detection task right at the edge layer, near the source of the attacks for quick response, versatility, as well as reducing the workload of the cloud. We also propose a multi attack detection mechanism called LocKedge Low Complexity Cyberattack Detection in IoT Edge Computing, which has low complexity for deployment at the edge zone while still maintaining high accuracy. LocKedge is implemented in two manners: centralized and federated learning manners in order to verify the performance of the architecture from different perspectives. The performance of our proposed mechanism is compared with that of other machine learning and deep learning methods using the most updated BoT IoT data set. The results show that LocKedge outperforms other algorithms such as NN, CNN, RNN, KNN, SVM, KNN, RF and Decision Tree in terms of accuracy and NN in terms of complexity.


page 1

page 9

page 11


STEC-IoT: A Security Tactic by Virtualizing Edge Computing on IoT

To a large extent, the deployment of edge computing (EC) can reduce the ...

Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G

Owing to the large volume of sensed data from the enormous number of IoT...

A Novel Sybil Attack Detection Scheme Based on Edge Computing for Mobile IoT Environment

Internet of things (IoT) connects all items to the Internet through info...

Software-Defined Edge Computing: A New Architecture Paradigm to Support IoT Data Analysis

The rapid deployment of Internet of Things (IoT) applications leads to m...

Five-Layers SDP-Based Hierarchical Security Paradigm for Multi-access Edge Computing

The rise in embedded and IoT device usage comes with an increase in LTE ...

Distributed Machine Learning for Predictive Analytics in Mobile Edge Computing Based IoT Environments

Predictive analytics in Mobile Edge Computing (MEC) based Internet of Th...

Machine Learning in the Internet of Things for Industry 4.0

Number of IoT devices is constantly increasing which results in greater ...