INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
In today’s era, Cloud services area unit distinguished among the non-public, public and business domains. Several of those services area unit expected to bealways on and have an important nature; so, security and resilience area unit progressively necessary aspects. As there is a huge growth of internet which increases major challenge is internet security. There is large amount of threats are evolved which harm our computer systems or internet security. There are various types of malwares are invented with small variant which is trying to damaged our computer system. Malware means malicious data. These malwares are come up with different files format like PE, EXE file etc. There are various antiviruses are available which scan the file and remove the malware. But now days the various malwares are emerged with some variants and the antiviruses are incapable to identify that malwares. For detecting any type of malware and one variation is that it also classifies the malware into their different families can be designed.For classification purpose it uses the SVM i.e. bolstersVector Machine algorithm.These systems use one class SVM because it provides better efficiency than two classes SVM. This approach provides high detection accuracy over 90%. It detects system as well as network level data depending upon type of threats [1].
Keywords:
Bolster vector machine, Static technique, Virtual Machine etc.
Cite Article:
"Malware Detection in Cloud Computing Infrastructure", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 1, page no.171 - 173, January-2019, Available :http://www.ijsdr.org/papers/IJSDR1901030.pdf
Downloads:
000336256
Publication Details:
Published Paper ID: IJSDR1901030
Registration ID:180924
Published In: Volume 4 Issue 1, January-2019
DOI (Digital Object Identifier):
Page No: 171 - 173
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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