research-article

IoT Cyber-Attack Detection: A Comparative Analysis

Authors:

Abdul Hanan K. Mohammed,

Hrag Jebamikyous,

Rasha KashefAuthors Info & Claims

DATA'21: International Conference on Data Science, E-learning and Information Systems 2021

Pages 117 - 123

https://doi.org/10.1145/3460620.3460742

Published: 04 June 2021 Publication History

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Abstract

A cyber-attack is precautious manipulation of computer systems and networks using malware to conciliate data or restrict processes or operations. These types of attacks are vastly growing over the years. This increase in structure and complexity calls for advanced innovation in defensive strategies and detection. Traditional approaches for detecting cyber-attacks suffer from low efficiency, especially with the high demands of increasing security threats. With the substitutional increase of computational power, machine learning and deep learning methods are considered significant solutions for defending and detecting those threats or attacks. In this paper, we performed a comparative analysis of IoT cyberattack detection methods. We utilized six different algorithms including, Random Forest, Logistic Regression, SVM, NB, KNN, and MLP. Each model is evaluated using precision, recall, F-score, and ROC.

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https://doi.org/10.1109/ACCESS.2024.3523530
Ibrahim NShehmir SYadav AKashef R(2025)A Transformer-Based Model for Network Intrusion Detection: Architecture, Classification Heads, and Transformer BlocksProceedings of IEMTRONICS 202410.1007/978-981-97-4780-1_12(149-163)Online publication date: 30-Jan-2025
https://doi.org/10.1007/978-981-97-4780-1_12
Mahesh BKaur S(2024)Exploring Machine Learning Algorithms for Detecting Cyber Attacks and Threats2024 9th International Conference on Communication and Electronics Systems (ICCES)10.1109/ICCES63552.2024.10860108(01-08)Online publication date: 16-Dec-2024
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Index Terms

IoT Cyber-Attack Detection: A Comparative Analysis

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Other conferences

DATA'21: International Conference on Data Science, E-learning and Information Systems 2021

April 2021

277 pages

ISBN:9781450388382

DOI:10.1145/3460620

Editors:
Juan Alfonso Lara Torralbo
UDIMA, Madrid, Spain
,
Shadi A. Aljawarneh
JUST, Jordan
,
Vangipuram Radhakrishna
VNRVJIET, India
,
Arun N.
JAIN, India

Copyright © 2021 ACM.

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Published: 04 June 2021

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DATA'21

DATA'21: International Conference on Data Science, E-learning and Information Systems 2021

April 5 - 7, 2021

Ma'an, Jordan

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Cited By

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https://doi.org/10.1109/ACCESS.2024.3523530
Ibrahim NShehmir SYadav AKashef R(2025)A Transformer-Based Model for Network Intrusion Detection: Architecture, Classification Heads, and Transformer BlocksProceedings of IEMTRONICS 202410.1007/978-981-97-4780-1_12(149-163)Online publication date: 30-Jan-2025
https://doi.org/10.1007/978-981-97-4780-1_12
Mahesh BKaur S(2024)Exploring Machine Learning Algorithms for Detecting Cyber Attacks and Threats2024 9th International Conference on Communication and Electronics Systems (ICCES)10.1109/ICCES63552.2024.10860108(01-08)Online publication date: 16-Dec-2024
https://doi.org/10.1109/ICCES63552.2024.10860108
Siva ONeeraja KKalyan DNaga K(2024)Cyber Attack Detection and Prediction System2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)10.1109/ACCAI61061.2024.10602219(1-8)Online publication date: 9-May-2024
https://doi.org/10.1109/ACCAI61061.2024.10602219
Alheeti KAlzahrani AJasim OAl-Dosary DAhmed HAl-Ani M(2023)Intelligent Detection System for Multi-Step Cyber-Attack Based on Machine Learning2023 15th International Conference on Developments in eSystems Engineering (DeSE)10.1109/DeSE58274.2023.10100226(510-514)Online publication date: 9-Jan-2023
https://doi.org/10.1109/DeSE58274.2023.10100226
Elmazi DKarras DAlkholidi AÇapari K(2023)Cybersecurity and Privacy Attacks Detection in IoT Networks with Improved Data Engineering and Machine Learning Methods2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (BigDataService)10.1109/BigDataService58306.2023.00046(223-228)Online publication date: Jul-2023
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Soleymanzadeh RAljasim MQadeer MKashef R(2022)Cyberattack and Fraud Detection Using Ensemble StackingAI10.3390/ai30100023:1(22-36)Online publication date: 18-Jan-2022
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Soleymanzadeh RKashef R(2022)The Future Roadmap for Cyber-attack Detection2022 6th International Conference on Cryptography, Security and Privacy (CSP)10.1109/CSP55486.2022.00021(66-70)Online publication date: Jan-2022
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Thapaliya SSharma P(2022)Cyber Forensic Investigation in IoT Using Deep Learning Based Feature Fusion in Big DataInternational Journal of Wireless Information Networks10.1007/s10776-022-00586-3Online publication date: 6-Dec-2022
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