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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 …
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
Data mining techniques have been concentrated for malware detection in the recent
decade. The battle between security analyzers and malware scholars is everlasting as …
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 …
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
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 …
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 …
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
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 …
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 …
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 & …
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
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 …
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
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 …
main concerns for the last few years. The smart devices are connected to communicate …