In this paper, a hybrid concentration based feature extraction (HCFE) approach is proposed.
The HCFE approach extracts the hybrid concentration (HC) of a sample in both the global …

Sažetak Computers have become increasingly vulnerable to malicious attacks with an
increase in popularity and the proliferation of open system architectures. There are …

The evolution of recent malicious software with the rising use of digital services has
increased the probability of corrupting data, stealing information, or other cybercrimes by …

Abstract Machine learning algorithms are widely used in malware detection where
successful analysis on static and dynamic features plays a crucial role in process of …

Malware detection relies on the discriminative power of machine learning to identify new
variants of malware samples. Automated malware detection, driven by machine learning …

Recent years have encountered massive growth in malwares which poses a severe threat to
modern computers and internet security. Existing malware detection systems are confronting …

Smartphones have started to take an essential place in every aspect of our lives with the
developing technology. All kinds of transactions, from daily routine work to business …

Detecting and preventing malware infections in systems is become a critical necessity. This
paper presents a hybrid method for malware detection, utilizing data mining algorithms such …

With the advent of internet-based technology, there has been a surge in internet-enabled
devices. These devices generate massive volumes of meaningful information to accomplish …

Malware data are typically depicted with extremely high-dimensional features, which lays an
excessive computational burden on detection methods. For the sake of effectiveness and …