Global outliers detection in wireless sensor networks: A novel approach integrating time‐series analysis, entropy, and random forest‐based classification.-Reference-Cited by-同舟云学术

Global outliers detection in wireless sensor networks: A novel approach integrating time‐series analysis, entropy, and random forest‐based classification.

Published:2021-09-15 Issue:1 Volume:52 Page:277-295
ISSN:0038-0644
Container-title:Software: Practice and Experience
language:en
Short-container-title:Softw: Pract Exper

Author:

Safaei Mahmood¹,Driss Maha²³^ORCID,Boulila Wadii³⁴^ORCID,Sundararajan Elankovan A.⁵,Safaei Mitra⁶

Affiliation:

1. 6G Innovation Centre University of Surrey Guildford UK

2. Security Engineering Lab Prince Sultan University Riyadh Saudi Arabia

3. RIADI Laboratory University of Manouba Manouba Tunisia

4. Robotics and Internet‐of‐Things Lab Prince Sultan University Riyadh Saudi Arabia

5. Center for Software Technology and Management, Faculty of Information Science and Technology University Kebangsaan Malaysia Selangor Malaysia

6. Fakultät Electronic und Informatik Gottfried Wilhelm Leibniz Universität Hannover Germany

Publisher

Wiley

Subject

Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/spe.3020

Reference54 articles.

1. Wireless sensor network survey

2. Wireless sensor networks: a survey

3. Identification of Outliers

4. Outliers in statistical data

5. Anomaly detection

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