A novel solutions for malicious code detection and family clustering based on machine learning

H Yang, S Li, X Wu, H Lu, W Han - IEEE Access, 2019 - ieeexplore.ieee.org
Malware has become a major threat to cyberspace security, not only because of the
increasing complexity of malware itself, but also because of the continuously created and …

Automatic malware classification and new malware detection using machine learning

L Liu, B Wang, B Yu, Q Zhong - Frontiers of Information Technology & …, 2017 - Springer
The explosive growth of malware variants poses a major threat to information security.
Traditional anti-virus systems based on signatures fail to classify unknown malware into their …

Malware family classification method based on static feature extraction

B Sun, Q Li, Y Guo, Q Wen, X Lin… - 2017 3rd IEEE …, 2017 - ieeexplore.ieee.org
With the development of malicious code engineering, new malware samples carry variability
and polymorphism, which makes the malware variants show an increasingly growing trend …

Cluster-oriented ensemble classifiers for intelligent malware detection

S Hou, L Chen, E Tas, I Demihovskiy… - Proceedings of the 2015 …, 2015 - ieeexplore.ieee.org
With explosive growth of malware and due to its damage to computer security, malware
detection is one of the cyber security topics that are of great interests. Many research efforts …

Unveiling zeus: automated classification of malware samples

A Mohaisen, O Alrawi - … of the 22nd International Conference on World …, 2013 - dl.acm.org
Malware family classification is an age old problem that many Anti-Virus (AV) companies
have tackled. There are two common techniques used for classification, signature based …

How to make attention mechanisms more practical in malware classification

X Ma, S Guo, H Li, Z Pan, J Qiu, Y Ding, F Chen - IEEE Access, 2019 - ieeexplore.ieee.org
Malware and its variants continue to pose a threat to network security. Machine learning has
been widely used in the field of malware classification, but some emerging studies, such as …

Evaluation of supervised machine learning techniques for dynamic malware detection

H Zhao, M Li, T Wu, F Yang - International Journal of Computational …, 2018 - Springer
Nowadays, security of the computer systems has become a major concern of security
experts. In spite of many antivirus and malware detection systems, the number of malware …

A survey on machine learning-based malware detection in executable files

J Singh, J Singh - Journal of Systems Architecture, 2021 - Elsevier
In last decade, a proliferation growth in the development of computer malware has been
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …

Malware classification using byte sequence information

B Jung, T Kim, EG Im - Proceedings of the 2018 Conference on …, 2018 - dl.acm.org
The number of new malware and new malware variants have been increasing continuously.
Security experts analyze malware to capture the malicious properties of malware and to …

An ensemble-based malware detection model using minimum feature set

I Zelinka, E Amer - Mendel, 2019 - flames.test.infv.eu
Current commercial antivirus detection engines still rely on signature-based methods.
However, with the huge increase in the number of new malware, current detection methods …