Malware Detection of Cloud Computing in Business Field - Analysis

This report delves into the critical issue of malware detection in cloud computing within a business context. It begins by highlighting the increasing sophistication of malware and the challenges faced by network operators and IT administrators in identifying and mitigating threats. The report explores the advantages of cloud computing for businesses, while also addressing the associated security risks, including denial-of-service attacks and malware injection. It investigates the processes behind malware attacks in cloud environments and examines various detection methods, such as signature-based and heuristic-based approaches, and the role of antivirus software. The report outlines project requirements, objectives, and potential challenges in implementing malware detection solutions, providing recommendations for overcoming these obstacles. The conclusion emphasizes the importance of proactive malware detection techniques to safeguard business operations and data in the cloud.

Running head: MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
Malware detection of cloud computing in business field
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MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
Table of Contents
Introduction......................................................................................................................................2
Problem domain and research questions..........................................................................................2
Background and project objective...................................................................................................3
Project Requirements Analysis and Specification...........................................................................4
Conclusion.......................................................................................................................................5
References........................................................................................................................................6
Appendix..........................................................................................................................................7

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MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
Introduction
Identifying malicious software is a complicated issue. There is an ever increasing
ecosystem of malicious software along with tools that represents daunting challenge for the
network operators and information technology administrator. It is important to develop proper
technique for malware detection in a business organization dealing with cloud computing. In
this perspective, antivirus software is considered as used tools in order to detect and stop
malicious and unwanted software (Klein 2017). The study deals with problem domain and
research questions arise in the business. In order to solve the issue, impact of malware detection
is analyzed in the present paper. In addition, project requirements analysis as well as
specification is discussed in the study.
Problem domain and research questions
Even though cloud computing provides several advantages in a business organization,
there are several issues involved with cloud computing (Dinh et al. 2013). As most of the
organizations like to move to adopt cloud computing, it has been the first choice for attacker on
internet. There are several types of attacks such as denial of service attacks, side channel attacks,
cloud malware injection attack occurred at present day. The malware attack needs adversary
creating own malicious service deployment module or virtual machine instance (Yan et al.
2016). It results attacker controlling the cloud system of the business and exploits its privileged
accessing the capabilities to the instances of service for attacking instance security domains of
the service. Thus, it is important to identify the type of attack and develop appropriate measures
that could be helpful to minimize the issues caused for malware in cloud computing (Hatem and
El-Khouly 2014).

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MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
The research questions can be described as followed.
 What are the processes of attacking in cloud computing by malware in cloud
computing of the business organization?
 How malware detection methods help to minimize the security threats in cloud
computing?
 What are the challenges might be faced for malware detection method implication
in the business organization?
 How the challenges can be overcome?
Background and project objective
Ferrara, Pistoia and Tripp (2015) stated that it is important to have appropriate malware
detection method in order to identify the malware attack and protect cloud computing of the
business organization. Malware detection methods are different types. As a network service of
malware detection, the capabilities are provided by host-based anti-virus software that can
efficiently and effectively provide as in-cloud network service. On the other hand, multi-
detection technique has an important role for malicious as well as unwanted software that need to
determine (Ko & Choo, 2015). Hence, it becomes crucial to identify the appropriate malware
detection method that can be helpful for the business organization.
Project Requirements Analysis and Specification
The project aims to identify the malware detection method suitable and appropriate for
the business in order to secure cloud computing (Mollah et al. 2017). Along with this, the project
objectives can be listed as followed.

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MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
 To find out the procedures of attacking in cloud computing by malware in cloud
computing
 To identify the malware detection minimizing security threats in cloud computing
 To analyze the challenges might be faced while implementing malware detection
methods in the business organization
 To recommend solutions for overcoming the issues
For the detection of malware in a system there is no requirement of hardware
specification. Any system can be used to run the anti-malware software’s. The top five anti-
malware software’s in the market has been reviewed below:
Bitfender Norton Kaspersky
Lab
Avira Avast
Best Feature Secure Delete 100%
Guarantee
Safe Banking Gaming
Mode
DNS
Redirecting
Loss in
Computer
Resource
97% 97% 93% 100% 88%
False
Positives
96% 95% 99% 99% 96%
Compatibility Windows 10
Windows 8
Windows 7
Mac
Windows 10
Windows 8
Windows 7
Mac
Windows 10
Windows 8
Windows 7
Mac
Windows 10
Windows 8
Windows 7
Windows 10
Windows 8
Windows 7
Mac
Vulnerable Yes Yes NA Yes Yes

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MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
Software
Detection
Minimum
Number of
Licenses
1 1 3 1 1
These are generally known as antivirus software’s. These software’s are able to monitor a
computer system for 24x7. They will do periodic scanning of malicious elements in the system
and remove them permanently from the system. Choosing of an antivirus is up to the decision of
oneself. It is the duty of the owner of the system owner to install a good anti-malware software to
safeguard them from harm. These software’s would work similarly on a cloud system. They
differ in versions and their capacity to stop the malware from harming the system (Hussein et al.
2017).
Conclusion
From the discussion, it concludes that it is important for a business organization keeping
the business safe and secured. In order to achieve this, business needs to identify appropriate
detection technique. Signature based malware detection; Heuristic based malware detection and
Specification based detection is the major types of prevention technique through which the
business organization can develop malware prevention method. However, several challenges
might be faced while implication that requires to eradicate by the professionals of the business
organization.

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MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
References
Dinh, H. T., Lee, C., Niyato, D., & Wang, P. (2013). A survey of mobile cloud computing:
architecture, applications, and approaches. Wireless communications and mobile
computing, 13(18), 1587-1611.
Ferrara, P., Pistoia, M., & Tripp, O. (2015). U.S. Patent Application No. 14/954,338.
Hatem, S. S., & El-Khouly, M. M. (2014). Malware detection in Cloud computing. International
Journal of Advanced Computer Science and Applications (IJACSA), 5.
Hussein, R. K., Alenezi, A., Atlam, H. F., Mohammed, M. Q., Walters, R. J., & Wills, G. B.
(2017). Toward confirming a framework for securing the virtual machine image in cloud
computing. Advances in Science, Technology and Engineering Systems Journal, 2(4), 44-50.
Klein, A. (2017). U.S. Patent No. 9,723,014. Washington, DC: U.S. Patent and Trademark
Office.
Ko, R., & Choo, R. (2015). The Cloud Security Ecosystem: Technical, Legal, Business and
Management Issues. Syngress.
Mollah, M. B., Azad, M. A. K., & Vasilakos, A. (2017). Security and privacy challenges in
mobile cloud computing: Survey and way ahead. Journal of Network and Computer
Applications.
Yan, Q., Yu, F. R., Gong, Q., & Li, J. (2016). Software-defined networking (SDN) and
distributed denial of service (DDoS) attacks in cloud computing environments: A survey, some
research issues, and challenges. IEEE Communications Surveys & Tutorials, 18(1), 602-622.

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MALWARE DETECTION OF CLOUD COMPUTING IN BUSINESS FIELD
Appendix
Article name Description
Advances in Science, Technology and
Engineering Systems Journal
Toward confirming a framework for securing
the virtual machine image in cloud
computing.
International Journal of Advanced Computer
Science and Applications
Malware detection in Cloud computing