A novel deep learning-based approach for malware detection
Malware detection approaches can be classified into two classes, including static analysis
and dynamic analysis. Conventional approaches of the two classes have their respective …
and dynamic analysis. Conventional approaches of the two classes have their respective …
An efficient densenet-based deep learning model for malware detection
Recently, there has been a huge rise in malware growth, which creates a significant security
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …
DF classification algorithm for constructing a small sample size of data-oriented DF regression model
The deep forest (DF) model is built using a multilayer ensemble of forest units through
decision tree aggregation. DF presents characteristics of an easy-to-understand structure, is …
decision tree aggregation. DF presents characteristics of an easy-to-understand structure, is …
Visualized malware multi-classification framework using fine-tuned CNN-based transfer learning models
There is a massive growth in malicious software (Malware) development, which causes
substantial security threats to individuals and organizations. Cybersecurity researchers …
substantial security threats to individuals and organizations. Cybersecurity researchers …
Robust malware family classification using effective features and classifiers
Malware development has significantly increased recently, posing a serious security risk to
both consumers and businesses. Malware developers continually find new ways to …
both consumers and businesses. Malware developers continually find new ways to …
Detection, characterization, and profiling DoH Malicious traffic using statistical pattern recognition
The domain name system (DNS) protocol has been used for over three decades. It plays a
vital role in the functioning of the Internet by facilitating the conversion of domain names into …
vital role in the functioning of the Internet by facilitating the conversion of domain names into …
Android malware detection and classification using LOFO feature selection and tree-based models
SA Roseline, S Geetha - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
Cybersecurity threats on mobile devices are also growing substantially with the subsequent
rise in the usage of smartphones and mobile applications. Cybercriminals inevitably have …
rise in the usage of smartphones and mobile applications. Cybercriminals inevitably have …
PAFE: A lightweight visualization-based fast malware classification method
S Li, J Wang, S Wang, Y Song - Heliyon, 2024 - cell.com
With the development of automated malware toolkits, cybersecurity faces evolving threats.
Although visualization-based malware analysis has proven to be an effective method …
Although visualization-based malware analysis has proven to be an effective method …
DF classification algorithm for constructing a small sample size of data-oriented DF regression model
The deep forest (DF) model is built using a multilayer ensemble of forest units through
decision tree aggregation. DF presents characteristics of an easy-to-understand structure, is …
decision tree aggregation. DF presents characteristics of an easy-to-understand structure, is …
An assessment of the effectiveness of pretrained neural networks for malware detection
EM Malvacio, JC Duarte - IEEE Latin America Transactions, 2023 - ieeexplore.ieee.org
The speed at which malware develops is much faster than analysts are able to analyze it,
and it is now a dangerous threat to businesses, critical infrastructure and individuals, forcing …
and it is now a dangerous threat to businesses, critical infrastructure and individuals, forcing …