International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 08 Issue: 08 | Aug 2021
www.irjet.net p-ISSN: 2395-0072
© 2021, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal
| Page 3357
accuracy can reach 97.8%. In the experiment, the
accuracy of detection decreased by no more than 3%,
and the effectiveness of
the evasion attack is much
better than in other recent studies. (Dai et al., 2019)
4.8 Deep Belief
The approach focuses on developing an efficient
computational framework based on Deep Belief
Networks for malware detection.
This framework
merges high level static analysis, dynamic analysis
and system calls in feature extraction in order to
achieve the highest accuracy.
The evaluation
compares the most familiar machine learning
approaches that were applied in malware detection
with this framework. The obtained results
demonstrate that Deep
Belief Networks technique
can realize 99.1% accuracy with the presented
dataset. There is a complete static analysis jar which
adapts different efficient methods in an attempt to
facilitate and speed up the static analysis by handling
all the Android applications in only one step rather
than considering one application at a time. (Saif et al.,
2018)
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