Deep Learning Approaches for Malware Detection in the Industrial Internet of Things: A Comprehensive Analysis

This survey aims to identify hazards associated with the Internet of Things (IoT), focusing on malware that can infiltrate various devices, applications, and systems within the Industrial Internet of Things (IIoT). Such malware enables malicious actors to manipulate these systems. This research utilizes deep learning as a method for detecting malicious programs. Additionally, it provides hypotheses and background information on deep learning and the IIoT, along with an overview of the types of malware that can compromise IoT applications. Finally, the study presents findings related to the research hypotheses and relevant topics.

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Published
2024-12-10
DOI
https://doi.org/10.1109/acit62805.2024.10877268
Primary Topic
Advanced Malware Detection Techniques
Type
article
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article

Deep Learning Approaches for Malware Detection in the Industrial Internet of Things: A Comprehensive Analysis

Mohammad Aljaidi, Ghassan Samara, Mohammed Mahmod Shuaib, Mohammad Abu Fadda et al.
Advanced Malware Detection Techniques
article

Deep Learning Approaches for Malware Detection in the Industrial Internet of Things: A Comprehensive Analysis

Mohammad Aljaidi, Ghassan Samara, Mohammed Mahmod Shuaib, Mohammad Abu Fadda, Mahmoud Odeh, Raed Alazaidah, Mohammad A. Kanan, Abeer Al-Mohtaseb, A. N.
article en

Abstract

This survey aims to identify hazards associated with the Internet of Things (IoT), focusing on malware that can infiltrate various devices, applications, and systems within the Industrial Internet of Things (IIoT). Such malware enables malicious actors to manipulate these systems. This research utilizes deep learning as a method for detecting malicious programs. Additionally, it provides hypotheses and background information on deep learning and the IIoT, along with an overview of the types of malware that can compromise IoT applications. Finally, the study presents findings related to the research hypotheses and relevant topics.

Zarqa University (JO), University of Business and Technology (SA)
Decent work and economic growth
Openalex Percentile: Top 70%
Advanced Malware Detection Techniques
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Deep Learning Approaches for Malware Detection in the Industrial Internet of Things: A Comprehensive Analysis — Mohammad Aljaidi, Ghassan Samara, et al. · (2024) | TGRS Research Map | TGRS