Handling Dual Threats- An Approach to Detect Backdoor Malware and DNS Spoofing Attacks in IoT

Internet of Things network is vulnerable to a multitude of cyber threats. Two recurring threats on IoT networks, i.e. Backdoor malware, and DNS spoofing, are taken into consideration in this manuscript. The result assessment comprised of three models - K Nearest Neighbour, Decision Tree, and Light Gradient Boosting Machine. With 94.7 percent accuracy and 91.9 percent F1 score, the LightGBM model performed the best, helping to address both kinds of threats.

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Publication Details

Published
2025-07-25
DOI
https://doi.org/10.1109/isac364032.2025.11156703
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Handling Dual Threats- An Approach to Detect Backdoor Malware and DNS Spoofing Attacks in IoT

Shyam Biswal, Kavita Sharma, Devpriya Panda, Neelamadhab Padhy et al.
Network Security and Intrusion Detection
article

Handling Dual Threats- An Approach to Detect Backdoor Malware and DNS Spoofing Attacks in IoT

Shyam Biswal, Kavita Sharma, Devpriya Panda, Neelamadhab Padhy, Abhishek Singh
article en

Abstract

Internet of Things network is vulnerable to a multitude of cyber threats. Two recurring threats on IoT networks, i.e. Backdoor malware, and DNS spoofing, are taken into consideration in this manuscript. The result assessment comprised of three models - K Nearest Neighbour, Decision Tree, and Light Gradient Boosting Machine. With 94.7 percent accuracy and 91.9 percent F1 score, the LightGBM model performed the best, helping to address both kinds of threats.

Galgotias University (IN), XIM University (IN), GIET University (IN)
Openalex Percentile: Top 72%
Network Security and Intrusion Detection
DOISourceOpenAlex
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Handling Dual Threats- An Approach to Detect Backdoor Malware and DNS Spoofing Attacks in IoT — Shyam Biswal, Kavita Sharma, et al. · (2025) | TGRS Research Map | TGRS