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SAMADroid: A Novel 3-Level Hybrid Malware Detection Model for Android Operating System [PDF]
IEEE Access, 2018 For the last few years, Android is known to be the most widely used operating system and this rapidly increasing popularity has attracted the malware developer's attention.
Saba Arshad +5 more
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Static Malware Detection Using Stacked BiLSTM and GPT-2
IEEE Access, 2022 In recent years, cyber threats and malicious software attacks have been escalated on various platforms. Therefore, it has become essential to develop automated machine learning methods for defending against malware.
Deniz Demirci +3 more
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MalFuzz: Coverage-guided fuzzing on deep learning-based malware classification model.
PLoS ONE, 2022 With the continuous development of deep learning, more and more domains use deep learning technique to solve key problems. The security issues of deep learning models have also received more and more attention.
Yuying Liu +4 more
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A Feasibility Study on Evasion Attacks Against NLP-Based Macro Malware Detection Algorithms
IEEE Access, 2023 Machine learning-based models for malware detection have gained prominence in order to detect obfuscated malware. These models extract malicious features and endeavor to classify samples as either malware or benign entities.
Mamoru Mimura, Risa Yamamoto
doaj +1 more source
IEEE Access, 2023 In recent studies, convolutional neural networks (CNNs) are mostly used as dynamic techniques for visualization-based malware classification and detection.
Mohamad Mulham Belal +1 more
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Sensors, 2021 Detection of unknown malware and its variants remains both an operational and a research challenge in the Internet of Things (IoT). The Internet of Medical Things (IoMT) is a particular type of IoT network which deals with communication through smart ...
Abdullah Shawan Alotaibi
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Evaluation of Survivability of the Automatically Obfuscated Android Malware
Applied Sciences, 2022 Malware is a growing threat to all mobile platforms and hundreds of new malicious applications are being detected every day. At the same time, the development of automated software obfuscation techniques allows for the easy production of new malware ...
Himanshu Patel +9 more
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A Proposed Artificial Intelligence Model for Android-Malware Detection
Informatics, 2023 There are a variety of reasons why smartphones have grown so pervasive in our daily lives. While their benefits are undeniable, Android users must be vigilant against malicious apps.
Fatma Taher +4 more
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Toward Hardware-Assisted Malware Detection Utilizing Explainable Machine Learning: A Survey
IEEE Access, 2023 Hardware joined the battle against malware by introducing secure boot architectures, malware-aware processors, and trusted platform modules. Hardware performance indicators, power profiles, and side channel information can be leveraged at run-time via ...
Yehya Nasser, Mohamad Nassar
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IoT malware detection architecture using a novel channel boosted and squeezed CNN
Scientific Reports, 2022 Interaction between devices, people, and the Internet has given birth to a new digital communication model, the internet of things (IoT). The integration of smart devices to constitute a network introduces many security challenges.
Muhammad Asam +7 more
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