Abstract
The Internet is considered to be as a rich platform
of information where many people get benefit from its access
but still they are being attacked by computer malwares and
various other threats which distract their normal work flow to
be carried out in an efficient manner. In this paper, we give an
overview of the efficient read aligner software termed as REAL
which is used for next generation sequencing. It reads
structures as a tool to detect computer Malware. Using this tools
a dynamic computer malware detection model has been
presented in this paper that can detect the malwares to prevent
attacks which might cause damaging or stealing sensitive
information. This model is inspired by REAL which is an
efficient read aligner for next generation sequencing for
processing biological data. New anti-Malware technologies are
introduced to the world by the clock, but at the same time new
malware techniques have also emerged to misuse these
technologies. Experimental results of this study shows that the
proposed system is efficient and it is a novel way for detecting
malware code embedded in different types of computer files,
using bioinformatics tools with consistency and accuracy in
detecting the malware and it was able to complete the
assignment in high speed without excessive memory usages.
of information where many people get benefit from its access
but still they are being attacked by computer malwares and
various other threats which distract their normal work flow to
be carried out in an efficient manner. In this paper, we give an
overview of the efficient read aligner software termed as REAL
which is used for next generation sequencing. It reads
structures as a tool to detect computer Malware. Using this tools
a dynamic computer malware detection model has been
presented in this paper that can detect the malwares to prevent
attacks which might cause damaging or stealing sensitive
information. This model is inspired by REAL which is an
efficient read aligner for next generation sequencing for
processing biological data. New anti-Malware technologies are
introduced to the world by the clock, but at the same time new
malware techniques have also emerged to misuse these
technologies. Experimental results of this study shows that the
proposed system is efficient and it is a novel way for detecting
malware code embedded in different types of computer files,
using bioinformatics tools with consistency and accuracy in
detecting the malware and it was able to complete the
assignment in high speed without excessive memory usages.
| Original language | English |
|---|---|
| Title of host publication | IACSIT International Journal of Engineering and Technology |
| Publisher | IACSIT International Journal of Engineering and Technology |
| Pages | 315 |
| Number of pages | 319 |
| Volume | 5 |
| Edition | 2 |
| Publication status | Published - 2013 |
Keywords
- Malware detection, pattern recognition,