A Review of Cloud-Based Malware Detection System: Opportunities, Advances and Challenges

A Review of Cloud-Based Malware Detection System: Opportunities, Advances and Challenges

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Submitted Feb 13, 2021
Published Mar 10, 2021
DOI https://doi.org/10.24018/ejeng.2021.6.3.2372
Abstract viewed = 1570 times
Issue
Vol. 6 No. 3 (2021)
Section
Articles

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  •   Ömer Aslan

    •    University of Siirt, Turkey
  •   Merve Ozkan-Okay

    •    University of Ankara, Turkey
  •   Deepti Gupta

    •    University of Texas at San Antonio, USA

Abstract

Cloud computing has an important role in all aspects of storing information and providing services online. It brings several advantages over traditional storing and sharing schema such as an easy access, on-request storage, scalability and decreasing cost. Using its rapidly developing technologies can bring many advantages to the protection of Internet of Things (IoT), Cyber-Physical Systems (CPS) from a variety of cyber-attacks, where IoT, CPS provides facilities to humans in their daily lives. Since malicious software (malware) is increasing exponentially and there is no well-known approach to detecting malware, the usage of cloud environments to detect malware can be a promising method. A new generation of malware is using advanced obfuscation and packing techniques to escape from detection systems. This situation makes almost impossible to detect complex malware by using a traditional detection approach. The paper presents an extensive review of cloud-based malware detection approach and provides a vision to understand the benefit of cloud for protection of IoT, CPS from cyber-attack. This research explains advantages and disadvantages of cloud environments in detecting malware and also proposes a cloud-based malware detection framework, which uses a hybrid approach to detect malware.


Keywords: Cloud computing, cloud malware detection, cyber-physical system, malware detection

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How to Cite
[1]
Aslan, Ömer, Ozkan-Okay, M. and Gupta, D. 2021. A Review of Cloud-Based Malware Detection System: Opportunities, Advances and Challenges. European Journal of Engineering and Technology Research. 6, 3 (Mar. 2021), 1–8. DOI:https://doi.org/10.24018/ejeng.2021.6.3.2372.