IoT malware: An attribute-based taxonomy, detection mechanisms and challenges

Author:

Victor Princy,Lashkari Arash Habibi,Lu Rongxing,Sasi Tinshu,Xiong Pulei,Iqbal Shahrear

Funder

National Research Council of Canada’s Artificial Intelligence for Logistics Program

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Reference316 articles.

1. Vasan D, Alazab M, Venkatraman S, Akram J, Qin Z (2020) Mthael: Cross-architecture IoT malware detection based on neural network advanced ensemble learning. IEEE Transactions on Computers 69(11):1654–1667. https://doi.org/10.1109/TC.2020.3015584

2. State of IoT 2021: Number of connected IoT devices growing 9% to 12.3 B. https://IoT-analytics.com/number-connected-IoT-devices/. Accessed 9 Jan 2022

3. Security HN. IoT malware attacks rose 700% during the pandemic. https://www.helpnetsecurity.com/2021/07/20/IoT-malware-attacks-rose. Accessed 10 Dec 2021

4. Mary DRK, Ko E, Kim SG, Yum SH, Shin SY, Park SH (2021) A systematic review on recent trends, challenges, privacy and security issues of underwater internet of things. Sensors 21(24). https://doi.org/10.3390/s21248262, https://www.mdpi.com/1424-8220/21/24/8262

5. Costin A, Zaddach J (2018) IoT malware: Comprehensive survey, analysis framework and case studies. BlackHat USA

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