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Machine learning aided malware detection for secure and smart manufacturing: a comprehensive analysis of the state of the art
In the last decade, the number of computer malware has grown rapidly. Currently,
cybercriminals typically use malicious software (malware) as a means of attacking industrial …
cybercriminals typically use malicious software (malware) as a means of attacking industrial …
A systematic literature review of android malware detection using static analysis
Android malware has been in an increasing trend in recent years due to the pervasiveness
of Android operating system. Android malware is installed and run on the smartphones …
of Android operating system. Android malware is installed and run on the smartphones …
DTMIC: Deep transfer learning for malware image classification
In the ever-changing cyber threat landscape, evolving malware threats demand a new
technique for their detection. This paper puts forward a strategy for distinguishing malware …
technique for their detection. This paper puts forward a strategy for distinguishing malware …
[HTML][HTML] Android mobile malware detection using machine learning: A systematic review
With the increasing use of mobile devices, malware attacks are rising, especially on Android
phones, which account for 72.2% of the total market share. Hackers try to attack …
phones, which account for 72.2% of the total market share. Hackers try to attack …
A novel permission-based Android malware detection system using feature selection based on linear regression
With the developments in mobile and wireless technology, mobile devices have become an
important part of our lives. While Android is the leading operating system in market share, it …
important part of our lives. While Android is the leading operating system in market share, it …
A novel machine learning approach for android malware detection based on the co-existence of features
E Odat, QM Yaseen - IEEE Access, 2023 - ieeexplore.ieee.org
This paper proposes a machine learning model based on the co-existence of static features
for Android malware detection. The proposed model assumes that Android malware …
for Android malware detection. The proposed model assumes that Android malware …
Malbertv2: Code aware bert-based model for malware identification
To proactively mitigate malware threats, cybersecurity tools, such as anti-virus and anti-
malware software, as well as firewalls, require frequent updates and proactive …
malware software, as well as firewalls, require frequent updates and proactive …
Self-supervised vision transformers for malware detection
Malware detection plays a crucial role in cyber-security with the increase in malware growth
and advancements in cyber-attacks. Previously unseen malware which is not determined by …
and advancements in cyber-attacks. Previously unseen malware which is not determined by …
Deep learning feature exploration for android malware detection
Android mobile devices and applications are widely deployed and used in industry and
smart city. Malware detection is one of the most powerful and effective approaches to …
smart city. Malware detection is one of the most powerful and effective approaches to …
Hybrid sequence‐based Android malware detection using natural language processing
N Zhang, J Xue, Y Ma, R Zhang… - International Journal of …, 2021 - Wiley Online Library
Android platform has been the target of attackers due to its openness and increasing
popularity. Android malware has explosively increased in recent years, which poses serious …
popularity. Android malware has explosively increased in recent years, which poses serious …