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 …

A state-of-the-art survey of malware detection approaches using data mining techniques

A Souri, R Hosseini - Human-centric Computing and Information Sciences, 2018 - Springer
Data mining techniques have been concentrated for malware detection in the recent
decade. The battle between security analyzers and malware scholars is everlasting as …

[HTML][HTML] MalDAE: Detecting and explaining malware based on correlation and fusion of static and dynamic characteristics

W Han, J Xue, Y Wang, L Huang, Z Kong, L Mao - computers & security, 2019 - Elsevier
It is a wide-spread way to detect malware by analyzing its behavioral characteristics based
on API call sequences. However, previous studies usually just focus on its static or dynamic …

An enhanced stacked LSTM method with no random initialization for malware threat hunting in safety and time-critical systems

AN Jahromi, S Hashemi… - … on Emerging Topics …, 2020 - ieeexplore.ieee.org
Malware detection is an increasingly important operational focus in cyber security,
particularly, given the fast pace of such threats (eg, new malware variants introduced every …

[HTML][HTML] MalInsight: A systematic profiling based malware detection framework

W Han, J Xue, Y Wang, Z Liu, Z Kong - Journal of Network and Computer …, 2019 - Elsevier
To handle the security threat faced by the widespread use of Internet of Things (IoT) devices
due to the ever-lasting increase of malware, the security researchers increasingly rely on …

Spam detection approach for secure mobile message communication using machine learning algorithms

L GuangJun, S Nazir, HU Khan… - Security and …, 2020 - Wiley Online Library
The spam detection is a big issue in mobile message communication due to which mobile
message communication is insecure. In order to tackle this problem, an accurate and …

Detection of malicious software by analyzing the behavioral artifacts using machine learning algorithms

J Singh, J Singh - Information and Software Technology, 2020 - Elsevier
Malicious software deliberately affects the computer systems. Malware are analyzed using
static or dynamic analysis techniques. Using these techniques, unique patterns are …

Retracted article: a survey on malware detection and classification

R Komatwar, M Kokare - Journal of Applied Security Research, 2021 - Taylor & Francis
We, the Editor and Publisher of Journal of Applied Security Research, have retracted the
following article, which was published in volume 16, issue 3, 2021: Rupali Komatwara & …

A Novel Approach to Malware Detection using Machine Learning and Image Processing

SR Ahmed, SJ Mohamed, MS Aljanabi… - Proceedings of the …, 2024 - dl.acm.org
Studies have emphasized the limitations of existing methods in effectively detecting
advanced strains of malware. To address this gap, this research presents a novel approach …

Convolution Neural Network‐Based Higher Accurate Intrusion Identification System for the Network Security and Communication

Z Gu, S Nazir, C Hong, S Khan - Security and Communication …, 2020 - Wiley Online Library
With the development of communication systems, information securities remain one of the
main concerns for the last few years. The smart devices are connected to communicate …